# general libraries
import pandas as pd
import numpy as np
import itertools
import scipy.stats as stats
import random
import statistics
import datetime
import re
import json
# data cleaning libraries
from collections import Counter
# !pip install smote-variants
import smote_variants
from imblearn.over_sampling import SMOTE
from sklearn.feature_selection import SelectKBest, mutual_info_classif, chi2
from sklearn.preprocessing import LabelEncoder, OrdinalEncoder, MinMaxScaler, MaxAbsScaler
# ML libraries
from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
from sklearn.linear_model import LogisticRegression
from sklearn.metrics import accuracy_score, f1_score, precision_score, recall_score, roc_auc_score, confusion_matrix, classification_report
from sklearn.model_selection import KFold, train_test_split
from sklearn.naive_bayes import GaussianNB
from sklearn.neighbors import KNeighborsClassifier
from sklearn.neural_network import MLPClassifier
from sklearn.svm import SVC
from sklearn.tree import DecisionTreeClassifier
# Visualization libraries
from matplotlib import pyplot
import matplotlib.pyplot as plt
import seaborn as sns
import plotly.express as px
now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))
Current date and time : 2021-06-04 17:26:25
# toggle to hide code
from IPython.display import HTML
HTML('''<script>
code_show=true;
function code_toggle() {
if (code_show){
$('div.input').hide();
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}
$( document ).ready(code_toggle);
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# center all images
from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot
init_notebook_mode(connected=True)
HTML("""
<style>
.output_png {
display: table-cell;
text-align: center;
vertical-align: middle;
}
</style>
""")
ENDSC Data
# all cases
all_cases = pd.read_excel("../Data/dataset/ENDOSC_1.xls", sheet_name="All cases")
# cleaned cases
cleaned_cases = pd.read_excel("../Data/dataset/ENDOSC_1_2_2.xls", sheet_name="All IBD")
cleaned_cases_og = cleaned_cases
cleaned_cases.head()
| Year | Lab No | Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | ... | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Confirmed diagnosis | Method of confirmation | Initial pathologists diagnosis | Observing pathologists diagnosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 90 | 8989 | 52.410959 | 1 | 0 | 0 | 2 | 5 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | UC | Endoscopy | IBD ?UC | Chronic idiopathic IBD - indeterminate |
| 1 | 92 | 10640 | 24.673973 | 1 | 1 | 0 | 0 | 7 | 1 | 0 | ... | 2 | 0 | 0 | 0 | 0 | 0 | Crohns | Resection | IBD indeterminate, active | Chronic idiopathic IBD - highly suggestive of ... |
| 2 | 92 | 7489 | 51.345205 | 0 | 1 | 0 | 1 | 7 | 1 | 0 | ... | 2 | 0 | 0 | 0 | 0 | 0 | Crohns | Endoscopy | IBD ?Crohns | Chronic idiopathic IBD - highly suggestive of ... |
| 3 | 91 | 8691 | 48.556164 | 1 | 1 | 0 | 2 | 6 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | UC | Resection | IBD indeterminate, active | Chronic idiopathic IBD - indeterminate |
| 4 | 90 | 14201 | 39.367123 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | ... | 0 | 1 | 0 | 0 | 0 | 0 | Crohns | Endoscopy | Non-specific inflammation, acute | Normal |
5 rows × 29 columns
# IBD_def = pd.read_excel("../Data/Column_Definitions.xlsx", sheet_name="IBD")
# IBD_def[["Data Column", "Definition", "In depth understanding"]]
cleaned_cases = cleaned_cases.drop(['Year', 'Lab No', 'Method of confirmation', 'Initial pathologists diagnosis', 'Observing pathologists diagnosis'],axis=1)
IBD Stages: Since the stages of UC is determined by the severity of symptoms, the classes are manually added based on symptoms.
Use decision trees to determine
Perhaps find a doctor who can provide some expertise into the stages? - check if this is possible (we would need multiple people to have statistically significance)
Data Transformation Since the data is already dummy coded, the transformation of it will be required for understanding the outcome after modeling.
transform_dict = [{"data":["Mucin depletion", "Crypt architecture"],
"definitions":[{
0: "Normal",
1: "Mild",
2: "Moderate",
3: "Severe"}]},
{"data": ["Cryptitis extent", "Crypt abscesses extent"],
"definitions": [{
0: "None",
1: "Little",
2: "Moderate",
3: "Marked"}]},
{"data": ["Lamina propria polymorphs"],
"definitions": [{
0: "Absent",
1: "Focal",
2: "Diffuse"}]},
{"data": ["Cryptitis polymorphs", "Crypt abscesses polymorphs"],
"definitions": [{
0: "None",
1: "Few",
2: "Several",
3: "Many"}]},
{"data": ["Epithelial changes"],
"definitions": [{
0: "Normal",
1: "Flattening ",
2: "Degeneration",
3: "Erosion"}]},
{"data": ["Mucosal surface"],
"definitions": [{
0: "Flat",
1: "Irregular",
2: "Villous projections"}]}]
Set Seed for consistency
random.seed(123)
Crypt architecture measures the severity of the deformation of the colon, which will also signify at what severity stage the cases are at. This is the column that will be used for determining cases severities.
cleaned_cases['Crypt architecture'].unique()
crypt_dict = {0:"normal",
1:"mild",
2:"moderate",
3:"severe"}
cleaned_cases['Severity of Crypt Arch'] = [crypt_dict[x] for x in cleaned_cases['Crypt architecture']]
'Severity of Crypt Arch' + 'diagnoses'
'Severity of Crypt Archdiagnoses'
convert data to object rather than int since these are categorical data.
def change_to_object(df, data_col):
df[data_col] = df[data_col].astype(object)
run = [change_to_object(cleaned_cases, c) for c in cleaned_cases.columns[3:]]
cleaned_cases['Crypt profiles'] = cleaned_cases['Crypt profiles'].astype('int')
cleaned_cases.dtypes
Age float64 Sex int64 Active inflammation? int64 Mucosal surface object Crypt architecture object Crypt profiles int32 Increased lamina propria cellularity? object Mild & superficial increase in lamina propria cellularity? object Increased lymphoid aggregates in lamina propria? object Patchy lamina propria cellularity? object Marked & transmucosal increase in lamina propria cellularity object Cryptitis extent object Cryptitis polymorphs object Crypt abscesses extent object Crypt abscesses polymorphs object Lamina propria polymorphs object Epithelial changes object Mucin depletion object Intraepithelial lymphocytes object Subepithelial collagen object Lamina propria granulomas object Submucosal granulomas object Basal histiocytic cells object Confirmed diagnosis object Severity of Crypt Arch object dtype: object
Clean Diagnosis: Strip data and Upper Case and ensure spelling of all are correct to prevent any separation of classes which are unnecessary.
print(cleaned_cases['Confirmed diagnosis'].unique())
cleaned_cases['Confirmed diagnosis'] = [c.strip().upper() for c in cleaned_cases['Confirmed diagnosis']]
print( cleaned_cases['Confirmed diagnosis'].unique())
['UC' 'Crohns' 'Crohns ' 'Uc'] ['UC' 'CROHNS']
#cleaned_cases.columns
#cleaned_cases["Method of confirmation"] = [x if x != "Endosocpy" else "Endoscopy" for x in cleaned_cases["Method of confirmation"]]
#cleaned_cases["Method of confirmation"].unique()
#cleaned_cases['Observing pathologists diagnosis'].unique()
#cleaned_cases['Initial pathologists diagnosis'].unique()
#cleaned_cases['Initial pathologists diagnosis'] = [d if d != "IBD ?Crohn's" else "IBD ?Crohns" for d in cleaned_cases['Initial pathologists diagnosis']]
#cleaned_cases['Initial pathologists diagnosis'] = [d if d not in ["Non-specific inflammation,chronic", "Non-specific inflammaton, chronic"] else "Non-specific inflammation, chronic" for d in cleaned_cases['Initial pathologists diagnosis']]
#cleaned_cases['Initial pathologists diagnosis'].sort_values().unique()
#cleaned_cases['Year'].sort_values().unique()
Missing/Duplicate Data Checks
There is no duplicates data
print(f'IBD duplicates: {cleaned_cases.duplicated().any()}')
IBD duplicates: True
There are no missing data values
print(f'IBD missing: {cleaned_cases.isnull().values.any()}')
IBD missing: False
Cross and coworkers randomly shuffled the dataset and split the first 540 cases as the train set and the lasts 269 cases as the test set.
X = cleaned_cases.drop('Confirmed diagnosis',axis=1)
y = cleaned_cases['Confirmed diagnosis']
X_train,X_test,y_train,y_test = train_test_split(X,y,test_size=269, random_state=123)
print(f'Train set has {X_train.shape[0]} rows and test set has {X_test.shape[0]} rows')
Train set has 375 rows and test set has 269 rows
Counter(y_train)
Counter({'UC': 285, 'CROHNS': 90})
#Counter(cleaned_cases['Initial pathologists diagnosis'])
The age is skewed towards the younger generations, and there are outliers of age under 15 and above 85. Since there is no proof that these age groups are errors opposed to only having a low count, they will be left in the data.
plt.figure(figsize=(10,10))
sns.distplot(cleaned_cases.Age.values, bins=50, kde=True)
plt.xlabel('Age', fontsize=12)
plt.show()
C:\ProgramData\Anaconda\lib\site-packages\seaborn\distributions.py:2557: FutureWarning: `distplot` is a deprecated function and will be removed in a future version. Please adapt your code to use either `displot` (a figure-level function with similar flexibility) or `histplot` (an axes-level function for histograms).
The data below shows that majority of the cases are from years 90-92 and 95-96. The other years have minimal contribution for years prior to year 90.
#plt.figure(figsize=(10,10))
#sns.distplot(cleaned_cases.Year.values, bins=50, kde=True)
#plt.xlabel('Year', fontsize=12)
#plt.show()
While the data is a mixture of both histology and endoscopy, but majority of the confirmation methods are endoscopy.
fig = px.histogram(cleaned_cases, x="Age", color='Sex')
fig.show()
Distribution of the dataset, where majority of the classes are UC and the remaining are split to normal and UC roughly evenly.
cd_gb = cleaned_cases.groupby("Confirmed diagnosis").count().reset_index()
fig = px.bar(cd_gb, x='Confirmed diagnosis', y='Sex')
fig.show()
# cd_gb
fig = px.histogram(cleaned_cases, x="Age", color='Confirmed diagnosis')
fig.show()
plt.figure(figsize=(10,10))
<Figure size 720x720 with 0 Axes>
<Figure size 720x720 with 0 Axes>
The correlation matrix is show below, which is no the same method which is used for continuous variable, but rather categorical variables.
corr_matrix = cleaned_cases.apply(lambda x : pd.factorize(x)[0]).corr(method='pearson', min_periods=1)
corr_matrix.head()
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Confirmed diagnosis | Severity of Crypt Arch | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Age | 1.000000 | -0.024630 | 0.000645 | 0.066984 | 0.024193 | -0.013297 | 0.025116 | -0.014794 | 0.030832 | 0.030682 | ... | 0.009706 | -0.005371 | -0.017000 | -0.014212 | NaN | -0.015907 | -0.019861 | 0.055083 | -0.015878 | 0.024193 |
| Sex | -0.024630 | 1.000000 | 0.012179 | 0.105066 | 0.000677 | 0.035672 | -0.001894 | 0.011948 | 0.010158 | -0.012239 | ... | -0.007131 | -0.005653 | 0.059029 | -0.033380 | NaN | -0.004193 | -0.006338 | 0.040239 | -0.113294 | 0.000677 |
| Active inflammation? | 0.000645 | 0.012179 | 1.000000 | 0.281825 | 0.066631 | 0.136076 | -0.694303 | 0.076122 | 0.320400 | 0.419807 | ... | 0.900782 | 0.526095 | 0.575044 | -0.044335 | NaN | 0.097917 | 0.018071 | 0.104854 | -0.079975 | 0.066631 |
| Mucosal surface | 0.066984 | 0.105066 | 0.281825 | 1.000000 | -0.060980 | 0.166125 | -0.278963 | -0.059369 | 0.025034 | -0.067872 | ... | 0.191447 | 0.228068 | 0.310093 | -0.026130 | NaN | -0.051666 | -0.040136 | 0.023768 | -0.229855 | -0.060980 |
| Crypt architecture | 0.024193 | 0.000677 | 0.066631 | -0.060980 | 1.000000 | 0.131529 | -0.129055 | -0.025416 | -0.104277 | 0.071958 | ... | 0.088256 | 0.076395 | 0.107059 | -0.004681 | NaN | 0.038857 | 0.032759 | -0.007064 | -0.010103 | 1.000000 |
5 rows × 25 columns
We see strong correlations between the symptoms. Specifically, there is a strong correlation between active inflammation and lamina propria polymorphs, which is investigated further below.
Many of the correlations are intuitively connected. For example, cryptis polymorphs and extent, since they are both related to the the fact of where there is inflammation in the linings of the stomach to the morphed cells of the glands.
One interesting obervation is the correlation of epithelial changes and the mucin depletions since the epithelial layer concerns the outter layer of the intestine and the mucin depletion primarily concerns with the inner side of the organ.
fig = px.imshow(corr_matrix)
fig.update_yaxes(visible=False, showticklabels=False)
fig.update_xaxes(visible=False, showticklabels=False)
fig.show()
Active inflammation and lamina propria polymorphs
Overall, the active inflamation makes sense considering if there is no inflammation, that there in turn would have no polymorphs. Since the inner linings are typically only shows to morph when there is inflammation, this is intuitive in the results.
sns.stripplot(x='Active inflammation?', y='Lamina propria polymorphs', data=cleaned_cases, jitter=True)
sns.despine()
%%time
sns.pairplot(cleaned_cases)
Wall time: 1min 36s
<seaborn.axisgrid.PairGrid at 0x22ada860400>
Odds ratio is a measure of association between an exposure and an outcome. The OR represents the odds that an outcome will occur given a particular exposure, compared to the odds of the outcome occurring in the absence of that exposure. source
There is no strong correlations between the two, that if a patient is of a specified year and age, there is a 1:1 ratio of the patient being diagnosed with UC of chrohns.
# odds ratio calc
uc_ch = cleaned_cases.loc[cleaned_cases["Confirmed diagnosis"].isin(['UC', 'CROHNS'])]
table_uc = uc_ch[["Confirmed diagnosis", "Sex", "Active inflammation?"]].groupby("Confirmed diagnosis").sum()#.values
print(table_uc)
oddsratio_uc, pvalue_uc = stats.fisher_exact(table_uc)
print("OddsR: ", round(oddsratio_uc,4), "p-Value:", pvalue_uc)
Sex Active inflammation? Confirmed diagnosis CROHNS 96 87 UC 205 283 OddsR: 1.5233 p-Value: 0.01851111505184613
Reducing categorical classes Since there isn't a high number of classes in each categorical columns, there is no need to reduce the number of classes in a categorical set.
Each column in the dataset is a symptom. SOme of the symptoms are rankings. When the column for Subepithelial collagen is 1 it means that the patient had that symptom and when it is 0 it means the patient did not have that symptom.
train = pd.concat([X_train,y_train],axis=1)
Get only the binary variables
binary_vars = X_train.columns[X_train.apply(lambda series: False if set(series)-{0,1} else True)]
binary_vars = list(set(binary_vars) - set(['Active inflammation?']))
# binary_vars
Calculate the relative risk ratio of having IBD if patient has or doesnt have Patchy lamina propria cellularity
patchyVsIbd = train.groupby(['Patchy lamina propria cellularity?','Confirmed diagnosis']).size()
patchySummary = X_train.groupby('Patchy lamina propria cellularity?').size()
print(patchyVsIbd)
print(patchySummary)
Patchy lamina propria cellularity? Confirmed diagnosis
0 CROHNS 63
UC 231
1 CROHNS 27
UC 54
dtype: int64
Patchy lamina propria cellularity?
0 294
1 81
dtype: int64
What proportion of those with patchy lamina propria had Crohn's Disease?
proportions = patchyVsIbd/patchySummary
proportions
Patchy lamina propria cellularity? Confirmed diagnosis
0 CROHNS 0.214286
UC 0.785714
1 CROHNS 0.333333
UC 0.666667
dtype: float64
How much more chance of getting Crohn's disease if you have patchy lamina propria cellularity VS if you dont have patch lamina prpria cellularity?
proportions.loc[1]/proportions.loc[0]
Confirmed diagnosis CROHNS 1.555556 UC 0.848485 dtype: float64
Observe above that the probabilit of getting Crohn's is twice as much if you have patchy lamina propria cellularity VS if you dont have patchy lamina.
Determine relative risk of Crohn's or UC for all the symptoms
Calculation will require creating 3 tables:
#1.Symptom, Is Symptom Present, Confirmed Diagnosis, Count
#Column, Value, Value for Diagnosis Column
binaryTrain = train[binary_vars+['Confirmed diagnosis']]
symptomDiagnosis = binaryTrain.reset_index().melt(id_vars=['index','Confirmed diagnosis'])
#Column, Value, Value for Diagnosis Column, Count
diseaseCountPerSymptom = symptomDiagnosis.groupby(['variable','value','Confirmed diagnosis']).size()
diseaseCountPerSymptom.head()
variable value Confirmed diagnosis
Basal histiocytic cells 0 CROHNS 86
UC 269
1 CROHNS 4
UC 16
Increased lamina propria cellularity? 0 CROHNS 36
dtype: int64
#2.Symptom, Is Symptom Present, Count
countPerSymptom = symptomDiagnosis.groupby(['variable','value']).size()
countPerSymptom.head()
variable value
Basal histiocytic cells 0 355
1 20
Increased lamina propria cellularity? 0 103
1 272
Increased lymphoid aggregates in lamina propria? 0 307
dtype: int64
#3. Symptom, Is Symptom Present, Confirmed Diagnosis, Proportion
proportionIbdPerSymptom = diseaseCountPerSymptom/countPerSymptom
proportionIbdPerSymptom.head()
variable value Confirmed diagnosis
Basal histiocytic cells 0 CROHNS 0.242254
UC 0.757746
1 CROHNS 0.200000
UC 0.800000
Increased lamina propria cellularity? 0 CROHNS 0.349515
dtype: float64
#4.Symptom, Confirmed Diagnosis, Relative Risk (Final Table)
propDf = proportionIbdPerSymptom.reset_index()
noSymptom = propDf.loc[propDf['value']==0].drop('value',axis=1).set_index(['variable','Confirmed diagnosis'])
yesSymptom = propDf.loc[propDf['value']==1].drop('value',axis=1).set_index(['variable','Confirmed diagnosis'])
'''
Some symptoms such as Submucosal granulomas are only present in Crohn's pateints. this means there is no
patient who has both submucosal granuloma and UC. So the risk of having UC given u have submcuoal granulomas
is 0. But currently in the yesSymptom df, the row Submucosal granulom and UC does not even exist. So if that row
is missing just add a row with 0
'''
noSymptom = noSymptom.reset_index()
varDxCombos= list(itertools.product(set(noSymptom['variable']),set(noSymptom['Confirmed diagnosis'])))
allCombos = pd.DataFrame(index=pd.MultiIndex.from_tuples(varDxCombos))
allCombos.index.names = ['variable','Confirmed diagnosis']
noSymptom = noSymptom.set_index(['variable','Confirmed diagnosis'])
yesSymptom = pd.merge(yesSymptom, allCombos, left_index=True, right_index=True, how='outer').fillna({0:0})
yesSymptom.head()
| 0 | ||
|---|---|---|
| variable | Confirmed diagnosis | |
| Basal histiocytic cells | CROHNS | 0.200000 |
| UC | 0.800000 | |
| Increased lamina propria cellularity? | CROHNS | 0.198529 |
| UC | 0.801471 | |
| Increased lymphoid aggregates in lamina propria? | CROHNS | 0.205882 |
Out of all the people that had Increased lamina propria cellularity, what percent of them had Crohn's disase?
In below table see that 22.5% of patients with Increased lamina propria cellularity had Crohn's disease.
Out of all the people that did NOT have Increase lamina propria cellularity, how many had Crohn's disease?
noSymptom = pd.merge(noSymptom, allCombos, left_index=True, right_index=True, how='outer').fillna({0:0})
noSymptom.head()
| 0 | ||
|---|---|---|
| variable | Confirmed diagnosis | |
| Basal histiocytic cells | CROHNS | 0.242254 |
| UC | 0.757746 | |
| Increased lamina propria cellularity? | CROHNS | 0.349515 |
| UC | 0.650485 | |
| Increased lymphoid aggregates in lamina propria? | CROHNS | 0.247557 |
You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?
You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?
relativeRiskIbd = (yesSymptom/noSymptom).reset_index()
relativeRiskIbd.head()
| variable | Confirmed diagnosis | 0 | |
|---|---|---|---|
| 0 | Basal histiocytic cells | CROHNS | 0.825581 |
| 1 | Basal histiocytic cells | UC | 1.055762 |
| 2 | Increased lamina propria cellularity? | CROHNS | 0.568015 |
| 3 | Increased lamina propria cellularity? | UC | 1.232112 |
| 4 | Increased lymphoid aggregates in lamina propria? | CROHNS | 0.831656 |
fig,ax = plt.subplots(nrows=1,ncols=2, sharey=True)
crohns = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='CROHNS']
uc = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='UC']
# normal = relativeRiskIbd[relativeRiskIbd['Confirmed diagnosis']=='NORMAL']
ax[0].barh(crohns['variable'],crohns[0])
ax[0].set(title='Crohns',
ylabel='SYMPTOMS')
ax[1].barh(uc['variable'],uc[0])
ax[1].set(title='UC',xlabel='Relative Risk of Diagnosis Given That Patient has this Symptom',)
#ax[2].barh(normal['variable'],normal[0])
# ax[2].set(title='Normal')
[Text(0.5, 1.0, 'UC'), Text(0.5, 0, 'Relative Risk of Diagnosis Given That Patient has this Symptom')]
For unsupervised EDA, The objective is to find multiple symptoms that are all 1 for the same patients and are all 0 for other patients.
If two symptoms are both positive in 1000 patients. And in another 1000 patients the two symptoms are negative. This would indicate correlation between those 2 symptoms.
exposure = 'Lamina propria granulomas'
disease = 'Increased lamina propria cellularity?'
risks = X_train.groupby([exposure,disease]
).size()/X_train.groupby([exposure]).size()
risks = risks.reset_index()
riskGivenNoExposure = risks.loc[(risks[exposure] == 0)&
(risks[disease] == 1),0].values[0]
riskGivenExposure = risks.loc[(risks[exposure] == 1)&
(risks[disease] == 1),0].values[0]
riskGivenExposure/riskGivenNoExposure
1.2046332046332047
Get the cross tab of every symptom with every other symptom
def multicolumn_crosstab(df,cols):
cols=sorted(cols)
dummies = pd.get_dummies(df[cols])
dfWithDummies = pd.concat([df,dummies],axis=1)
dfWithDummies = dfWithDummies.reset_index()
dfMelt = dfWithDummies.melt(id_vars=np.concatenate([np.array(['index']),dummies.columns.values]),
value_vars=cols)
dfMelt = dfMelt.drop('index',axis=1)
levelGroup = dfMelt.groupby(['variable','value'])
crosstab = levelGroup.sum()
countPerLevel = levelGroup.size()
crossTabProp = crosstab.divide(countPerLevel,axis=0)
return crossTabProp
ct = multicolumn_crosstab(X_train.astype(str),binary_vars)
In the below cross tab, the value in the second row, and in the fourth column (Incerased Lamina propria cellularity_1) is the number 0.894737. This means that 89% of the patients (in the train set) had both Basal histocytic cells and Increased lamina propria cellularity. Notice how this number 89% adds up tihe the 10.5263 % on the left of it. That 10% number is the proportion of patients that had basal histocytic cells but did NOT have icnreased lamina propria cellularity.
ct.head()
| Basal histiocytic cells_0 | Basal histiocytic cells_1 | Increased lamina propria cellularity?_0 | Increased lamina propria cellularity?_1 | Increased lymphoid aggregates in lamina propria?_0 | Increased lymphoid aggregates in lamina propria?_1 | Intraepithelial lymphocytes_0 | Intraepithelial lymphocytes_1 | Lamina propria granulomas_0 | Lamina propria granulomas_1 | ... | Marked & transmucosal increase in lamina propria cellularity_1 | Mild & superficial increase in lamina propria cellularity?_0 | Mild & superficial increase in lamina propria cellularity?_1 | Patchy lamina propria cellularity?_0 | Patchy lamina propria cellularity?_1 | Sex_0 | Sex_1 | Subepithelial collagen_0 | Submucosal granulomas_0 | Submucosal granulomas_1 | ||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| variable | value | |||||||||||||||||||||
| Basal histiocytic cells | 0 | 1.000000 | 0.000000 | 0.284507 | 0.715493 | 0.814085 | 0.185915 | 0.974648 | 0.025352 | 0.963380 | 0.036620 | ... | 0.329577 | 0.991549 | 0.008451 | 0.800000 | 0.200000 | 0.523944 | 0.476056 | 1.0 | 0.988732 | 0.011268 |
| 1 | 0.000000 | 1.000000 | 0.100000 | 0.900000 | 0.900000 | 0.100000 | 1.000000 | 0.000000 | 0.900000 | 0.100000 | ... | 0.300000 | 1.000000 | 0.000000 | 0.500000 | 0.500000 | 0.750000 | 0.250000 | 1.0 | 1.000000 | 0.000000 | |
| Increased lamina propria cellularity? | 0 | 0.980583 | 0.019417 | 1.000000 | 0.000000 | 1.000000 | 0.000000 | 0.980583 | 0.019417 | 0.980583 | 0.019417 | ... | 0.000000 | 1.000000 | 0.000000 | 1.000000 | 0.000000 | 0.533981 | 0.466019 | 1.0 | 1.000000 | 0.000000 |
| 1 | 0.933824 | 0.066176 | 0.000000 | 1.000000 | 0.750000 | 0.250000 | 0.974265 | 0.025735 | 0.952206 | 0.047794 | ... | 0.452206 | 0.988971 | 0.011029 | 0.702206 | 0.297794 | 0.536765 | 0.463235 | 1.0 | 0.985294 | 0.014706 | |
| Increased lymphoid aggregates in lamina propria? | 0 | 0.941368 | 0.058632 | 0.335505 | 0.664495 | 1.000000 | 0.000000 | 0.977199 | 0.022801 | 0.951140 | 0.048860 | ... | 0.400651 | 0.990228 | 0.009772 | 0.745928 | 0.254072 | 0.537459 | 0.462541 | 1.0 | 0.986971 | 0.013029 |
5 rows × 21 columns
Which feature is most correlated with the other features?
Observe that "Increased lamina propria cellularity" and "Active Inflammation" are the columns that is most correlated with the other symptoms.
noExposureDf: Get all the risks of getting Symptom B given that you dont have symptom A.
exposureDf: Get all the risks of getting Symptom B given that you do have symptom A.
crossTab = ct.reset_index()
noExposureDf = crossTab.loc[crossTab['value']=='0']
exposureDf = crossTab.loc[crossTab['value']=='1']
Divide all the risk-given-exposure/ risk-given-no-exposure to get the relative risk for every symptom pair
noExposureDf = noExposureDf.set_index('variable').drop('value',axis=1)
exposureDf = exposureDf.set_index('variable').drop('value',axis=1)
relativeRisks= exposureDf/noExposureDf
relativeRisks.head()
| Basal histiocytic cells_0 | Basal histiocytic cells_1 | Increased lamina propria cellularity?_0 | Increased lamina propria cellularity?_1 | Increased lymphoid aggregates in lamina propria?_0 | Increased lymphoid aggregates in lamina propria?_1 | Intraepithelial lymphocytes_0 | Intraepithelial lymphocytes_1 | Lamina propria granulomas_0 | Lamina propria granulomas_1 | ... | Marked & transmucosal increase in lamina propria cellularity_1 | Mild & superficial increase in lamina propria cellularity?_0 | Mild & superficial increase in lamina propria cellularity?_1 | Patchy lamina propria cellularity?_0 | Patchy lamina propria cellularity?_1 | Sex_0 | Sex_1 | Subepithelial collagen_0 | Submucosal granulomas_0 | Submucosal granulomas_1 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| variable | |||||||||||||||||||||
| Basal histiocytic cells | 0.000000 | inf | 0.351485 | 1.257874 | 1.105536 | 0.537879 | 1.026012 | 0.000000 | 0.934211 | 2.730769 | ... | 0.910256 | 1.008523 | 0.0 | 0.625000 | 2.500000 | 1.431452 | 0.525148 | 1.0 | 1.011396 | 0.0 |
| Increased lamina propria cellularity? | 0.952315 | 3.408088 | 0.000000 | inf | 0.750000 | inf | 0.993557 | 1.325368 | 0.971061 | 2.461397 | ... | inf | 0.988971 | inf | 0.702206 | inf | 1.005214 | 0.994026 | 1.0 | 0.985294 | inf |
| Increased lymphoid aggregates in lamina propria? | 1.031040 | 0.501634 | 0.000000 | 1.504902 | 0.000000 | inf | 0.993235 | 1.289916 | 1.051370 | 0.000000 | ... | 0.000000 | 1.009868 | 0.0 | 1.281467 | 0.173643 | 0.985027 | 1.017399 | 1.0 | 1.013201 | 0.0 |
| Intraepithelial lymphocytes | 1.057803 | 0.000000 | 0.805281 | 1.074214 | 0.948889 | 1.232323 | 0.000000 | inf | 0.924242 | 2.904762 | ... | 1.016667 | 1.008264 | 0.0 | 0.991870 | 1.029536 | 0.616162 | 1.452381 | 1.0 | 1.011050 | 0.0 |
| Lamina propria granulomas | 0.912281 | 2.666667 | 0.475248 | 1.204633 | 1.232877 | 0.000000 | 0.954545 | 3.000000 | 0.000000 | inf | ... | 0.000000 | 1.008403 | 0.0 | 0.164384 | 4.588235 | 0.865979 | 1.156627 | 1.0 | 0.802228 | 72.0 |
5 rows × 21 columns
The relative risk from our risk matrix is the same as the one when we manually calculated it. 1.559171
relativeRisks.loc['Lamina propria granulomas','Increased lamina propria cellularity?_1' ]
1.2046332046332047
Replace infinity values or abnormally high Relative risks with 0
relativeRisks = relativeRisks.applymap(lambda cell:0 if cell>20 else cell)
Observe in heatmap below that Submucosal granulomas are highly correlated with lamina propria granulomas
symptomPresent = [column for column in ct.columns if '1' in column]
sns.heatmap(relativeRisks[symptomPresent])
<AxesSubplot:ylabel='variable'>
Out of the 453 patients that did not have patchy lamina propria cellularity none of those patients also had lamina propria granulomas.
However, out of the 87 patients that had patchy laminap propria cellularity, 4 of those patients also had lamina propria granulomas.
It looks like these 2 columns are correlated.
X_train.groupby(['Patchy lamina propria cellularity?','Submucosal granulomas']).size()
Patchy lamina propria cellularity? Submucosal granulomas
0 0 294
1 0 77
1 4
dtype: int64
Out of the 453 patients that did not have patchy lamina propria cellularity only 1 of those patients also had lamina propria granulomas.
However, out of the 87 patients that had patchy laminap propria cellularity, 12 of those patients also had lamina propria granulomas.
It looks like these 2 columns are correlated.
X_train.groupby(['Patchy lamina propria cellularity?','Lamina propria granulomas']).size()
Patchy lamina propria cellularity? Lamina propria granulomas
0 0 292
1 2
1 0 68
1 13
dtype: int64
You have two people, one with increased lamina propria cellularity and the other one without increased lamina propria cellularity. How much more likely is the first person to have Crohn's disease compared to the second?
train.groupby(['Submucosal granulomas','Confirmed diagnosis']).size()
Submucosal granulomas Confirmed diagnosis
0 CROHNS 86
UC 285
1 CROHNS 4
dtype: int64
The model assumptions for all models are not concerning to the data for visualization. The main requirement is that the data doesn't have a linear correlation between features and that the data is independent, assumed by the unique data points.
Due to the data primarily being categorical, the modifications/assumptions are difficult to decipher.
Dummy coding the Data
There are two different set methods, dummy coding and ordinal. Before converting to dummy code, the data is first returned to it original form, then dummy coded to understand the effects of feature reduction and whether its required.
# convert it back to the original setup
df_reset = cleaned_cases.copy()
df_reset_od = cleaned_cases.copy()
df_reset.head()
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Confirmed diagnosis | Severity of Crypt Arch | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 52.410959 | 1 | 0 | 0 | 2 | 5 | 1 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | UC | moderate |
| 1 | 24.673973 | 1 | 1 | 0 | 0 | 7 | 1 | 0 | 0 | 0 | ... | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | CROHNS | normal |
| 2 | 51.345205 | 0 | 1 | 0 | 1 | 7 | 1 | 0 | 0 | 0 | ... | 2 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | CROHNS | mild |
| 3 | 48.556164 | 1 | 1 | 0 | 2 | 6 | 1 | 0 | 0 | 1 | ... | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | UC | moderate |
| 4 | 39.367123 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | CROHNS | normal |
5 rows × 25 columns
transform_dict
[{'data': ['Mucin depletion', 'Crypt architecture'],
'definitions': [{0: 'Normal', 1: 'Mild', 2: 'Moderate', 3: 'Severe'}]},
{'data': ['Cryptitis extent', 'Crypt abscesses extent'],
'definitions': [{0: 'None', 1: 'Little', 2: 'Moderate', 3: 'Marked'}]},
{'data': ['Lamina propria polymorphs'],
'definitions': [{0: 'Absent', 1: 'Focal', 2: 'Diffuse'}]},
{'data': ['Cryptitis polymorphs', 'Crypt abscesses polymorphs'],
'definitions': [{0: 'None', 1: 'Few', 2: 'Several', 3: 'Many'}]},
{'data': ['Epithelial changes'],
'definitions': [{0: 'Normal',
1: 'Flattening ',
2: 'Degeneration',
3: 'Erosion'}]},
{'data': ['Mucosal surface'],
'definitions': [{0: 'Flat', 1: 'Irregular', 2: 'Villous projections'}]}]
for val in transform_dict:
print("============new dictionary===========")
cols = val['data']
print(val['definitions'])
for col in cols:
try:
df_reset[col] = [val['definitions'][0][v] for v in df_reset[col]]
except:
pass
============new dictionary===========
[{0: 'Normal', 1: 'Mild', 2: 'Moderate', 3: 'Severe'}]
============new dictionary===========
[{0: 'None', 1: 'Little', 2: 'Moderate', 3: 'Marked'}]
============new dictionary===========
[{0: 'Absent', 1: 'Focal', 2: 'Diffuse'}]
============new dictionary===========
[{0: 'None', 1: 'Few', 2: 'Several', 3: 'Many'}]
============new dictionary===========
[{0: 'Normal', 1: 'Flattening ', 2: 'Degeneration', 3: 'Erosion'}]
============new dictionary===========
[{0: 'Flat', 1: 'Irregular', 2: 'Villous projections'}]
# review the data transformation
df_reset[["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion"]]
# get dummies
dummied = pd.get_dummies(df_reset[["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion","Severity of Crypt Arch"]])
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis",
df_dummy = pd.merge(dummied, cleaned_cases.drop(["Cryptitis extent","Cryptitis polymorphs","Crypt abscesses extent","Crypt abscesses polymorphs","Lamina propria polymorphs","Epithelial changes","Mucin depletion", "Severity of Crypt Arch"], axis=1), how = "inner", left_index=True, right_index=True)
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis",
df_dummy
| Cryptitis extent_Little | Cryptitis extent_Marked | Cryptitis extent_Moderate | Cryptitis extent_None | Cryptitis polymorphs_Few | Cryptitis polymorphs_Many | Cryptitis polymorphs_None | Cryptitis polymorphs_Several | Crypt abscesses extent_Little | Crypt abscesses extent_Marked | ... | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | Marked & transmucosal increase in lamina propria cellularity | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Confirmed diagnosis | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | ... | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | UC |
| 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | CROHNS |
| 2 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | CROHNS |
| 3 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | UC |
| 4 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | CROHNS |
| ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... | ... |
| 639 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | UC |
| 640 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | UC |
| 641 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | UC |
| 642 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | UC |
| 643 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | ... | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | UC |
644 rows × 48 columns
for column "Initial pathologists diagnosis_?IBD ?Infective", there is only one instance of this observation. Due to this we will drop the column as it will error during analysis.
#df_dummy = df_dummy.drop(["Initial pathologists diagnosis_?IBD ?Infective","Initial pathologists diagnosis_Pouchitis", "Initial pathologists diagnosis_Diversion colitis", "Initial pathologists diagnosis_IBD indeterminate, quiescent"] ,axis=1)
df_type = pd.DataFrame(df_dummy.dtypes)
for x in df_type.loc[df_type[0] == "uint8"].reset_index()['index']:
df_dummy[x] = df_dummy[x].astype('object')
df_dummy.dtypes
Cryptitis extent_Little object Cryptitis extent_Marked object Cryptitis extent_Moderate object Cryptitis extent_None object Cryptitis polymorphs_Few object Cryptitis polymorphs_Many object Cryptitis polymorphs_None object Cryptitis polymorphs_Several object Crypt abscesses extent_Little object Crypt abscesses extent_Marked object Crypt abscesses extent_Moderate object Crypt abscesses extent_None object Crypt abscesses polymorphs_Few object Crypt abscesses polymorphs_Many object Crypt abscesses polymorphs_None object Crypt abscesses polymorphs_Several object Lamina propria polymorphs_Absent object Lamina propria polymorphs_Diffuse object Lamina propria polymorphs_Focal object Epithelial changes_Degeneration object Epithelial changes_Erosion object Epithelial changes_Flattening object Epithelial changes_Normal object Mucin depletion_Mild object Mucin depletion_Moderate object Mucin depletion_Normal object Mucin depletion_Severe object Severity of Crypt Arch_mild object Severity of Crypt Arch_moderate object Severity of Crypt Arch_normal object Severity of Crypt Arch_severe object Age float64 Sex int64 Active inflammation? int64 Mucosal surface object Crypt architecture object Crypt profiles int32 Increased lamina propria cellularity? object Mild & superficial increase in lamina propria cellularity? object Increased lymphoid aggregates in lamina propria? object Patchy lamina propria cellularity? object Marked & transmucosal increase in lamina propria cellularity object Intraepithelial lymphocytes object Subepithelial collagen object Lamina propria granulomas object Submucosal granulomas object Basal histiocytic cells object Confirmed diagnosis object dtype: object
Ordinal Data
Ordinal data is the method of which the data is already set up in. This allows the researchers to put the remaining data types into an ordinal set up for analysis.
ord_cols = ["Severity of Crypt Arch"]
# "Method of confirmation","Initial pathologists diagnosis","Observing pathologists diagnosis",
for val in ord_cols:
print(val)
array_un = df_reset_od[val].unique().tolist()
df_reset_od[val] = df_reset_od[val].apply(lambda x: array_un.index(x))
Severity of Crypt Arch
df_ordinal = df_reset_od
df_ordinal.head()
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Confirmed diagnosis | Severity of Crypt Arch | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 52.410959 | 1 | 0 | 0 | 2 | 5 | 1 | 0 | 1 | 0 | ... | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | UC | 0 |
| 1 | 24.673973 | 1 | 1 | 0 | 0 | 7 | 1 | 0 | 0 | 0 | ... | 2 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | CROHNS | 1 |
| 2 | 51.345205 | 0 | 1 | 0 | 1 | 7 | 1 | 0 | 0 | 0 | ... | 2 | 3 | 2 | 0 | 0 | 0 | 0 | 0 | CROHNS | 2 |
| 3 | 48.556164 | 1 | 1 | 0 | 2 | 6 | 1 | 0 | 0 | 1 | ... | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | UC | 0 |
| 4 | 39.367123 | 0 | 0 | 0 | 0 | 7 | 0 | 0 | 0 | 0 | ... | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | CROHNS | 1 |
5 rows × 25 columns
Of the two differing methods, one of the two will be selected for analysis.
#X_ord = df_ordinal.drop(columns=["Observing pathologists diagnosis", "Initial pathologists diagnosis", "Confirmed diagnosis"], axis=1)
X_ord = df_ordinal.drop(columns=["Confirmed diagnosis"], axis=1)
y_ord = df_ordinal['Confirmed diagnosis']
X_train_ord , X_test_ord, y_train_ord, y_test_ord = train_test_split(X_ord, y_ord, test_size=0.25, random_state=42)
X_train_ord[X_train_ord.isna().any(axis=1)]
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Crypt abscesses polymorphs | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Severity of Crypt Arch |
|---|
0 rows × 24 columns
Max-Min Transformation
df_ord_scale = df_reset_od.drop("Confirmed diagnosis", 1)
X_train_ord = X_train_ord.copy().reset_index().drop('index',axis=1)
X_test_ord = X_test_ord.copy().reset_index().drop('index',axis=1)
for val in X_train_ord.columns:
X_train_ord[val] = X_train_ord[val].astype(int)
X_test_ord[val] = X_test_ord[val].astype(int)
# Scale only columns that have values greater than 1
to_scale = [col for col in X_train_ord.columns if X_train_ord[col].max() > 1]
mms = MinMaxScaler()
scaled = mms.fit_transform(X_train_ord[to_scale])
scaled = pd.DataFrame(scaled, columns=to_scale)
scaled_test = mms.fit_transform(X_test_ord[to_scale])
scaled_test = pd.DataFrame(scaled_test, columns=to_scale)
# Replace original columns with scaled ones
for col in scaled:
X_train_ord[col] = scaled[col]
X_test_ord[col] = scaled_test[col]
# df_ord_scale = X_train_ord.merge(df_reset_od["Confirmed diagnosis"], how="inner", left_index=True, right_index=True)
# X_train_ord = X_train_ord.merge(df_reset_od["Confirmed diagnosis"], how="inner", left_index=True, right_index=True)
X_train_ord[X_train_ord.isna().any(axis=1)]
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Crypt abscesses polymorphs | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Severity of Crypt Arch |
|---|
0 rows × 24 columns
X_test_ord[X_test_ord.isna().any(axis=1)]
| Age | Sex | Active inflammation? | Mucosal surface | Crypt architecture | Crypt profiles | Increased lamina propria cellularity? | Mild & superficial increase in lamina propria cellularity? | Increased lymphoid aggregates in lamina propria? | Patchy lamina propria cellularity? | ... | Crypt abscesses polymorphs | Lamina propria polymorphs | Epithelial changes | Mucin depletion | Intraepithelial lymphocytes | Subepithelial collagen | Lamina propria granulomas | Submucosal granulomas | Basal histiocytic cells | Severity of Crypt Arch |
|---|
0 rows × 24 columns
SMOTE
sm = SMOTE(random_state=123)
X_sm, y_sm = sm.fit_resample(X_train_ord, y_train_ord)
print('MixMax Scaler')
print(f'''Shape of X before SMOTE: {X_ord.shape}
Shape of X after SMOTE: {X_sm.shape}''')
MixMax Scaler Shape of X before SMOTE: (644, 24) Shape of X after SMOTE: (706, 24)
print('\nBalance of positive and negative classes (%):')
y_sm.value_counts(normalize=True) * 100
Balance of positive and negative classes (%):
CROHNS 50.0 UC 50.0 Name: Confirmed diagnosis, dtype: float64
# Final Sets
data = [X_sm, X_test_ord, y_sm, y_test_ord]
msm = smote_variants.MSMOTE(proportion=28, random_state = 123)
X_msm, y_msm = msm.sample(X_train_ord.values, y_train_ord.values)
X_msm = pd.DataFrame(columns = X_train_ord.columns, data=X_msm)
y_msm = pd.Series(data = y_msm)
msm2 = smote_variants.MSMOTE(proportion=1, random_state = 123)
X_msm, y_msm = msm2.sample(X_msm.values, y_msm.values)
X_msm = pd.DataFrame(columns = X_train_ord.columns, data=X_msm)
y_msm = pd.Series(data = y_msm)
2021-06-04 17:31:35,375:INFO:MSMOTE: Running sampling via ('MSMOTE', "{'proportion': 28, 'n_neighbors': 5, 'n_jobs': 1, 'random_state': 123}")
2021-06-04 17:31:35,643:INFO:MSMOTE: Running sampling via ('MSMOTE', "{'proportion': 1, 'n_neighbors': 5, 'n_jobs': 1, 'random_state': 123}")
fs = SelectKBest(score_func=chi2, k='all')
fs.fit(X_sm.to_numpy() , y_sm.to_numpy() )
X_train_fs = fs.transform(X_sm.to_numpy() )
X_test_fs = fs.transform(X_test_ord.to_numpy())
df_features = pd.DataFrame()
df_features['Features'] = X_test_ord.columns
df_features['Scores'] = np.round(fs.scores_,2)
df_features = df_features.sort_values('Scores', ascending=False)
# plot the scores
ax = sns.barplot(x="Scores", y="Features", data=df_features)
# fit the model
# data = [X_sm, X_test_ord, y_sm, y_test_ord]
model = LogisticRegression(solver='lbfgs')
t = model.fit(X_sm, y_sm)
# evaluate the model
yhat = model.predict(X_test_ord)
# evaluate predictions
accuracy = accuracy_score(y_test_ord, yhat)
print('Accuracy: %.2f' % (accuracy*100))
Accuracy: 65.22
assigned = y_sm.unique()
assigned
array(['CROHNS', 'UC'], dtype=object)
df_logit = pd.DataFrame()
df_logit['Attributes'] = X_sm.columns
for l in range(0, len(model.coef_)):
df_logit['data_'+str(assigned[1])] = abs(model.coef_[l])
df_logit = df_logit.sort_values(by='data_UC', ascending = False)
# plot the scores
ax = sns.barplot(x="data_UC", y="Attributes", data=df_logit)
ax = sns.barplot(x="data_UC", y="Attributes", data=df_logit)
# ax = sns.barplot(x="data_NORMAL", y="Attributes", data=df_logit)
confirmed to not be needed considering time constraint.
modelCompare = {'model': [], 'features': [], 'accuracy': [], 'f1': [],
'precision': [], 'recall': [], 'params': []}
def hyper_search(modelDictionary, modelParamDictionary, data, features):
# define empty dictionaries to start
modelAccuracy = 0
bestModel = {}
df_tmp = pd.DataFrame()
modelCompare = pd.DataFrame()
features1 = ', '.join(map(str, features))
# iterate through the model dictionary to execute each model
for key, value in modelDictionary.items():
accuracyDics = {}
finalResults = {}
print(f'\r\nProcessing Model: {key}')
# get the hyper parameter dictionary listings for the specific model
paramDictionary = modelParamDictionary[key]
# build out all permutations
keys, values = zip(*paramDictionary.items())
paramList = [dict(zip(keys, v)) for v in itertools.product(*values)]
for dic in paramList:
finalResults = main(value, data, dic)
accuracyDics.update(groupClassifiers(finalResults))
bestScore = 0
avgAccuracy = 0
plotScore = {}
for k in accuracyDics:
for a in accuracyDics[k][0]:
k1 = {}
k1 = k[:k.index('(')]
avgAccuracy = statistics.mean(accuracyDics[k][0]['accuracy'])
avgF1 = statistics.mean(accuracyDics[k][0]['f1'])
avgPrecision = statistics.mean(accuracyDics[k][0]['precision'])
avgRecall = statistics.mean(accuracyDics[k][0]['recall'])
param = accuracyDics[k][0]['params']
if avgAccuracy > bestScore:
bestScore = avgAccuracy
plotScore.clear()
plotScore = {'classifier': k1,
'features': features1,
'accuracy': accuracyDics[k][0]['accuracy'],
'avgAccuracy': avgAccuracy,
'f1': accuracyDics[k][0]['f1'],
'avgF1': avgF1,
'precision': accuracyDics[k][0]['precision'],
'avgPrecision': avgPrecision,
'recall': accuracyDics[k][0]['recall'],
'avgRecall': avgRecall,
'params': param}
#plot_models(plotScore)
df_tmp = pd.DataFrame({'model': plotScore['classifier'],
'features': plotScore['features'],
'accuracy': plotScore['avgAccuracy'],
'f1': plotScore['avgF1'],
'precision': plotScore['avgPrecision'],
'recall': plotScore['avgRecall'],
'params': plotScore['params']})
modelCompare = modelCompare.append(df_tmp, ignore_index=True)
df_tmp = df_tmp[0:0]
print(f'*****************************************************')
print(f'* {key}')
print(f'* Best Params Result: ')
print(f'* {plotScore}')
print(f'*****************************************************')
if bestScore > modelAccuracy:
modelAccuracy = avgAccuracy
bestModel.clear()
bestModel = plotScore
print(f'*****************************************************')
print(f'* Best Performing Model and Params is:')
print(f'* {bestModel}')
print(f'*****************************************************')
print(f'\r\n{modelCompare}')
def main(clfr, data, clfrHyperParams={}):
X_, y_, n_folds = data
kf = KFold(n_splits=n_folds)
ret = {}
for id, (trainIndex, testIndex) in enumerate(kf.split(X_, y_)):
clf = clfr(**clfrHyperParams)
clf.fit(X_[trainIndex], y_[trainIndex])
pred = clf.predict(X_[testIndex])
ret[id] = {'classifier': clf,
'accuracy': accuracy_score(y_[testIndex], pred),
'f1': f1_score(y_[testIndex], pred, average='weighted'),
'precision': precision_score(y_[testIndex], pred, average='micro'),
'recall': recall_score(y_[testIndex], pred, average='micro'),
'params': clf.get_params(deep=True)}
#print(classification_report(pred, y_[testIndex]))
return ret
def groupClassifiers(resultsDict):
accuraccyDict = {}
for key in resultsDict:
c = resultsDict[key]['classifier']
a = resultsDict[key]['accuracy']
f = resultsDict[key]['f1']
p = resultsDict[key]['precision']
r = resultsDict[key]['recall']
params = resultsDict[key]['params']
c_ = str(c).strip()
# Then check if the string value 'c_' exists as a key in the dictionary
if c_ in accuraccyDict:
accuraccyDict[c_][0]['accuracy'].append(a)
accuraccyDict[c_][0]['f1'].append(f)
accuraccyDict[c_][0]['precision'].append(p)
accuraccyDict[c_][0]['recall'].append(r)
else:
accuraccyDict[c_] = [{'accuracy': [a], 'f1': [f],
'precision': [p], 'recall': [r],
'params': [params]}]
return(accuraccyDict)
def plot_models(accuraccyDict):
plt.rcParams.update ({'text.usetex': False,
'font.family': 'stixgeneral',
'mathtext.fontset': 'stix'})
# create a new histogram with a given dictionary key's values
fig = plt.figure(figsize=(8, 8))
ax = fig.add_subplot(1, 1, 1)
plt.hist(accuraccyDict['accuracy'], facecolor='green', alpha=0.75, bins=8)
plt.text(.20, .5, 'Accuracy Score: ' + str(accuraccyDict['avgAccuracy']) + '\nF1 Score: ' + str(accuraccyDict['avgF1']))
ax.set_title(accuraccyDict['classifier'], fontsize=15)
ax.set_xlabel('Classifer Accuracy (By K-Fold)', fontsize=15)
ax.set_ylabel('Frequency', fontsize=15)
ax.xaxis.set_ticks(np.arange(0, 1.1, 0.1))
ax.yaxis.set_ticks(np.arange(0, .5, 1))
ax.xaxis.set_tick_params(labelsize=15)
ax.yaxis.set_tick_params(labelsize=15)
plt.subplots_adjust(left=0.125, right=0.9, bottom=0.1,
top=0.6, wspace=0.2, hspace=0.2)
plt.show()
modelDictionary = {
'RandomForestClassifier': RandomForestClassifier,
'KNeighborsClassifier': KNeighborsClassifier,
'LogisticRegression': LogisticRegression,
'GaussianNB': GaussianNB,
'AdaBoostClassifier': AdaBoostClassifier,
'DecisionTreeClassifier': DecisionTreeClassifier,
'SVC': SVC,
'MLPClassifier': MLPClassifier
}
modelParamsDictionary = {
'RandomForestClassifier': { # https://sklearn.org/modules/generated/sklearn.ensemble.RandomForestClassifier.html
'n_estimators': [200, 500, 700],
'criterion': ['gini', 'entropy'],
'max_features': ["auto", "sqrt", "log2"],
'bootstrap': [True],
'oob_score': [True, False],
'n_jobs': [-1]
},
'KNeighborsClassifier': { # https://sklearn.org/modules/generated/sklearn.neighbors.KNeighborsClassifier.html
'n_neighbors': np.arange(12, 18),
'weights': ['uniform', 'distance'],
'algorithm': ['auto', 'ball_tree', 'kd_tree', 'brute'],
'n_jobs': [-1]
},
'LogisticRegression': { # https://sklearn.org/modules/generated/sklearn.linear_model.LogisticRegression.html
'C': [0.0001, 0.001, 1],
'solver': ['newton-cg', 'lbfgs'],
'multi_class': ['ovr', 'multinomial'],
'max_iter': [100, 1000],
'n_jobs': [-1]
},
'GaussianNB': { # https://sklearn.org/modules/naive_bayes.html#gaussian-naive-bayes
'var_smoothing': [1e-9]
},
'AdaBoostClassifier': { # https://sklearn.org/modules/generated/sklearn.ensemble.AdaBoostClassifier.html
'n_estimators': [20, 50, 100, 300],
'learning_rate': [1]
},
'DecisionTreeClassifier': { # https://sklearn.org/modules/generated/sklearn.tree.DecisionTreeClassifier.html
'criterion': ['gini', 'entropy'],
'splitter': ['best', 'random'],
'max_features': ["auto", "sqrt", "log2"]
},
'SVC': { # https://sklearn.org/modules/generated/sklearn.svm.SVC.html
'C': [0.0001, 0.001, 1.0],
'kernel': ['linear'],
'gamma': ['scale', 'auto'],
'cache_size': [4000]
},
'MLPClassifier': { # https://sklearn.org/modules/generated/sklearn.neural_network.MLPClassifier.html
'activation': ['identity', 'logistic'],
'solver': ['adam'],
'learning_rate': ['constant', 'invscaling', 'adaptive'],
'max_iter': [5000, 7000, 9000]
}
}
now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))
Current date and time : 2021-06-05 09:02:04
n_folds = 5
l = len(df_features['Features']) - 1
df = df_features['Features']
# SMOTE Dataset
X = pd.concat([X_sm, X_test_ord]) #.to_numpy()
y = pd.concat([y_sm, y_test_ord]).to_numpy()
#data = (X, y, n_folds)
print('********************************************')
print('Starting SMOTE data set....')
print('********************************************')
for i in range(l ,6 , -1):
col = []
col = df[:i]
nX = X.loc[:, col]
nX = nX.to_numpy()
data = (nX, y, n_folds)
hyper_search(modelDictionary, modelParamsDictionary, data, col)
********************************************
Starting SMOTE data set....
********************************************
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.778552920071756, 'f1': [0.7513006208760027, 0.809542780416137, 0.7881332879972798, 0.9085173501577286, 0.7188681233776127], 'avgF1': 0.7952724325649522, 'precision': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.778552920071756, 'recall': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.778552920071756, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgAccuracy': 0.7462959271809182, 'f1': [0.7614140312830404, 0.7269124058660326, 0.8098284444609322, 0.8766233766233766, 0.6945299026787184], 'avgF1': 0.77386163218242, 'precision': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgPrecision': 0.7462959271809182, 'recall': [0.7528735632183908, 0.7011494252873564, 0.8092485549132948, 0.7803468208092486, 0.6878612716763006], 'avgRecall': 0.7462959271809182, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgAccuracy': 0.648169556840077, 'f1': [0.6727523667809623, 0.7007398731536663, 0.7575712193301322, 0.6536964980544747, 0.6754816535722745], 'avgF1': 0.692048322178302, 'precision': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgPrecision': 0.648169556840077, 'recall': [0.6609195402298851, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6647398843930635], 'avgRecall': 0.648169556840077, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgAccuracy': 0.5866985582353332, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6083727447889298], 'avgF1': 0.5370210108736294, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgPrecision': 0.5866985582353332, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgRecall': 0.5866985582353332, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgAccuracy': 0.7207893163244967, 'f1': [0.7487416194991541, 0.7853084951776985, 0.7915524562923408, 0.7730496453900708, 0.6761087339122022], 'avgF1': 0.7549521900542933, 'precision': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgPrecision': 0.7207893163244967, 'recall': [0.7413793103448276, 0.7758620689655172, 0.791907514450867, 0.630057803468208, 0.6647398843930635], 'avgRecall': 0.7207893163244967, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7520297654640887, 'f1': [0.7370073707540847, 0.7780496848350018, 0.7441433449703351, 0.8980891719745221, 0.7109950617364541], 'avgF1': 0.7736569268540796, 'precision': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7520297654640887, 'recall': [0.7298850574712644, 0.764367816091954, 0.7456647398843931, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7520297654640887, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgAccuracy': 0.575343830974686, 'f1': [0.6435917379656038, 0.7209330675066161, 0.706315018674652, 0.30392156862745096, 0.6777699519114003], 'avgF1': 0.6105062689371447, 'precision': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgPrecision': 0.575343830974686, 'recall': [0.632183908045977, 0.6954022988505747, 0.7052023121387283, 0.1791907514450867, 0.6647398843930635], 'avgRecall': 0.575343830974686, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgAccuracy': 0.6619958806723806, 'f1': [0.69462582219584, 0.7154500671742051, 0.7572254335260116, 0.664092664092664, 0.6925765699788141], 'avgF1': 0.704794111393507, 'precision': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgPrecision': 0.6619958806723806, 'recall': [0.6839080459770115, 0.6896551724137931, 0.7572254335260116, 0.49710982658959535, 0.6820809248554913], 'avgRecall': 0.6619958806723806, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.778552920071756, 'f1': [0.7513006208760027, 0.809542780416137, 0.7881332879972798, 0.9085173501577286, 0.7188681233776127], 'avgF1': 0.7952724325649522, 'precision': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.778552920071756, 'recall': [0.7471264367816092, 0.8045977011494253, 0.791907514450867, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.778552920071756, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.778553 0.795272 0.778553 0.778553
1 0.746296 0.773862 0.746296 0.746296
2 0.648170 0.692048 0.648170 0.648170
3 0.586699 0.537021 0.586699 0.586699
4 0.720789 0.754952 0.720789 0.720789
5 0.752030 0.773657 0.752030 0.752030
6 0.575344 0.610506 0.575344 0.575344
7 0.661996 0.704794 0.661996 0.661996
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7739352866919141, 'f1': [0.7460770183694619, 0.809542780416137, 0.7999036608863198, 0.8980891719745221, 0.7059631398632363], 'avgF1': 0.7919151543019355, 'precision': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7739352866919141, 'recall': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7739352866919141, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgAccuracy': 0.7463092153345293, 'f1': [0.7392199876814629, 0.7372040475488753, 0.8099685414953629, 0.8802588996763754, 0.6985286449786023], 'avgF1': 0.7730360242761357, 'precision': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgPrecision': 0.7463092153345293, 'recall': [0.7298850574712644, 0.7126436781609196, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgRecall': 0.7463092153345293, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgAccuracy': 0.6493189821274333, 'f1': [0.6671455938697318, 0.7110521992222772, 0.7631828519322299, 0.6484375, 0.6754816535722745], 'avgF1': 0.6930599597193027, 'precision': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgPrecision': 0.6493189821274333, 'recall': [0.6551724137931034, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgRecall': 0.6493189821274333, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgAccuracy': 0.5866985582353332, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6083727447889298], 'avgF1': 0.5370210108736294, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgPrecision': 0.5866985582353332, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.6994219653179191], 'avgRecall': 0.5866985582353332, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgAccuracy': 0.7162181914822935, 'f1': [0.7162071512876903, 0.7769116254290009, 0.8209431319487592, 0.7730496453900708, 0.6702185023409096], 'avgF1': 0.7514660112792861, 'precision': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgPrecision': 0.7162181914822935, 'recall': [0.7068965517241379, 0.764367816091954, 0.8208092485549133, 0.630057803468208, 0.6589595375722543], 'avgRecall': 0.7162181914822935, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgAccuracy': 0.7381436449405355, 'f1': [0.7555943058513662, 0.7692864045654093, 0.7441433449703351, 0.8802588996763754, 0.6626681671696762], 'avgF1': 0.7623902244466324, 'precision': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgPrecision': 0.7381436449405355, 'recall': [0.7528735632183908, 0.7528735632183908, 0.7456647398843931, 0.7861271676300579, 0.653179190751445], 'avgRecall': 0.7381436449405355, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgAccuracy': 0.5592120124908644, 'f1': [0.6363903285293359, 0.6850557771961477, 0.7352264963289916, 0.22564102564102562, 0.6665109396848238], 'avgF1': 0.589764913476065, 'precision': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgPrecision': 0.5592120124908644, 'recall': [0.6264367816091954, 0.6551724137931034, 0.7341040462427746, 0.12716763005780346, 0.653179190751445], 'avgRecall': 0.5592120124908644, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgAccuracy': 0.6516244767789515, 'f1': [0.6894341290893015, 0.6954022988505747, 0.763487329101577, 0.6431372549019608, 0.6866719413801271], 'avgF1': 0.6956265906647082, 'precision': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgPrecision': 0.6516244767789515, 'recall': [0.6781609195402298, 0.6666666666666666, 0.7630057803468208, 0.47398843930635837, 0.6763005780346821], 'avgRecall': 0.6516244767789515, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7739352866919141, 'f1': [0.7460770183694619, 0.809542780416137, 0.7999036608863198, 0.8980891719745221, 0.7059631398632363], 'avgF1': 0.7919151543019355, 'precision': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7739352866919141, 'recall': [0.7413793103448276, 0.8045977011494253, 0.8034682080924855, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7739352866919141, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.773935 0.791915 0.773935 0.773935
1 0.746309 0.773036 0.746309 0.746309
2 0.649319 0.693060 0.649319 0.649319
3 0.586699 0.537021 0.586699 0.586699
4 0.716218 0.751466 0.716218 0.716218
5 0.738144 0.762390 0.738144 0.738144
6 0.559212 0.589765 0.559212 0.559212
7 0.651624 0.695627 0.651624 0.651624
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgAccuracy': 0.7750847119792705, 'f1': [0.7460770183694619, 0.8158374552210141, 0.7943811144786455, 0.8980891719745221, 0.7124443868748527], 'avgF1': 0.7933658293836993, 'precision': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgPrecision': 0.7750847119792705, 'recall': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgRecall': 0.7750847119792705, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgAccuracy': 0.7451597900471729, 'f1': [0.7392199876814629, 0.7318084132477162, 0.8099685414953629, 0.8802588996763754, 0.6985286449786023], 'avgF1': 0.7719568974159039, 'precision': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgPrecision': 0.7451597900471729, 'recall': [0.7298850574712644, 0.7068965517241379, 0.8092485549132948, 0.7861271676300579, 0.6936416184971098], 'avgRecall': 0.7451597900471729, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgAccuracy': 0.648169556840077, 'f1': [0.6612784074000162, 0.7110521992222772, 0.7631828519322299, 0.6484375, 0.6754816535722745], 'avgF1': 0.6918865224253595, 'precision': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgPrecision': 0.648169556840077, 'recall': [0.6494252873563219, 0.6839080459770115, 0.7630057803468208, 0.4797687861271676, 0.6647398843930635], 'avgRecall': 0.648169556840077, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgAccuracy': 0.7150023254268819, 'f1': [0.7481985464666768, 0.7914596897355518, 0.7971484175626274, 0.7598566308243728, 0.6547897831134825], 'avgF1': 0.7502906135405423, 'precision': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgPrecision': 0.7150023254268819, 'recall': [0.7413793103448276, 0.7816091954022989, 0.7976878612716763, 0.6127167630057804, 0.6416184971098265], 'avgRecall': 0.7150023254268819, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
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* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgAccuracy': 0.7474719287754966, 'f1': [0.697476362625139, 0.7612131434282859, 0.7739653795697847, 0.9254658385093167, 0.6719024880623272], 'avgF1': 0.7660046424389707, 'precision': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgPrecision': 0.7474719287754966, 'recall': [0.6896551724137931, 0.7471264367816092, 0.7745664739884393, 0.861271676300578, 0.6647398843930635], 'avgRecall': 0.7474719287754966, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
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* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgAccuracy': 0.5580559431267025, 'f1': [0.6355735479569788, 0.6850557771961477, 0.7295077122643383, 0.22564102564102562, 0.6665109396848238], 'avgF1': 0.5884578005486628, 'precision': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgPrecision': 0.5580559431267025, 'recall': [0.6264367816091954, 0.6551724137931034, 0.7283236994219653, 0.12716763005780346, 0.653179190751445], 'avgRecall': 0.5580559431267025, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgAccuracy': 0.6562354660819879, 'f1': [0.6894341290893015, 0.7059056678557273, 0.7752517979992833, 0.6484375, 0.680730512429674], 'avgF1': 0.6999519214747972, 'precision': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgPrecision': 0.6562354660819879, 'recall': [0.6781609195402298, 0.6781609195402298, 0.7745664739884393, 0.4797687861271676, 0.6705202312138728], 'avgRecall': 0.6562354660819879, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgAccuracy': 0.7750847119792705, 'f1': [0.7460770183694619, 0.8158374552210141, 0.7943811144786455, 0.8980891719745221, 0.7124443868748527], 'avgF1': 0.7933658293836993, 'precision': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgPrecision': 0.7750847119792705, 'recall': [0.7413793103448276, 0.8103448275862069, 0.7976878612716763, 0.815028901734104, 0.7109826589595376], 'avgRecall': 0.7750847119792705, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.775085 0.793366 0.775085 0.775085
1 0.745160 0.771957 0.745160 0.745160
2 0.648170 0.691887 0.648170 0.648170
3 0.589011 0.538441 0.589011 0.589011
4 0.715002 0.750291 0.715002 0.715002
5 0.747472 0.766005 0.747472 0.747472
6 0.558056 0.588458 0.558056 0.558056
7 0.656235 0.699952 0.656235 0.656235
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7796890572055013, 'f1': [0.756521894452929, 0.8207461462740112, 0.7888626829315445, 0.9050632911392403, 0.7093979325981428], 'avgF1': 0.7961183894791736, 'precision': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7796890572055013, 'recall': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7796890572055013, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
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* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgAccuracy': 0.7416982260314929, 'f1': [0.7335910291247274, 0.7318084132477162, 0.8039733628606461, 0.8802588996763754, 0.6922203519024327], 'avgF1': 0.7683704113623796, 'precision': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgPrecision': 0.7416982260314929, 'recall': [0.7241379310344828, 0.7068965517241379, 0.8034682080924855, 0.7861271676300579, 0.6878612716763006], 'avgRecall': 0.7416982260314929, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgAccuracy': 0.6493455584346555, 'f1': [0.6555716060888476, 0.7005450064667237, 0.7575712193301322, 0.6536964980544747, 0.6964013504527086], 'avgF1': 0.6927571360785774, 'precision': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgPrecision': 0.6493455584346555, 'recall': [0.6436781609195402, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6878612716763006], 'avgRecall': 0.6493455584346555, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
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* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgAccuracy': 0.7184373131353399, 'f1': [0.759908658632525, 0.8060579417292026, 0.7971484175626274, 0.7642857142857142, 0.6386013066534284], 'avgF1': 0.7532004077726996, 'precision': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgPrecision': 0.7184373131353399, 'recall': [0.7528735632183908, 0.7988505747126436, 0.7976878612716763, 0.6184971098265896, 0.6242774566473989], 'avgRecall': 0.7184373131353399, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgAccuracy': 0.7416517174938543, 'f1': [0.7534992584352984, 0.7429641097818438, 0.7654029810350493, 0.8802588996763754, 0.6844438119544635], 'avgF1': 0.7653138121766061, 'precision': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgPrecision': 0.7416517174938543, 'recall': [0.7471264367816092, 0.7241379310344828, 0.7687861271676301, 0.7861271676300579, 0.6820809248554913], 'avgRecall': 0.7416517174938543, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5545943791110225, 'f1': [0.6355735479569788, 0.6798662051724348, 0.7295077122643383, 0.18848167539267016, 0.6773916573765312], 'avgF1': 0.5821641596325906, 'precision': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5545943791110225, 'recall': [0.6264367816091954, 0.6494252873563219, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5545943791110225, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgAccuracy': 0.6597169623280845, 'f1': [0.6893358876117496, 0.6951566951566953, 0.7693804268948776, 0.6536964980544747, 0.7083970705689648], 'avgF1': 0.7031933156573524, 'precision': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgPrecision': 0.6597169623280845, 'recall': [0.6781609195402298, 0.6666666666666666, 0.7687861271676301, 0.48554913294797686, 0.6994219653179191], 'avgRecall': 0.6597169623280845, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7796890572055013, 'f1': [0.756521894452929, 0.8207461462740112, 0.7888626829315445, 0.9050632911392403, 0.7093979325981428], 'avgF1': 0.7961183894791736, 'precision': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7796890572055013, 'recall': [0.7528735632183908, 0.8160919540229885, 0.791907514450867, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7796890572055013, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.779689 0.796118 0.779689 0.779689
1 0.741698 0.768370 0.741698 0.741698
2 0.649346 0.692757 0.649346 0.649346
3 0.589011 0.538441 0.589011 0.589011
4 0.718437 0.753200 0.718437 0.718437
5 0.741652 0.765314 0.741652 0.741652
6 0.554594 0.582164 0.554594 0.554594
7 0.659717 0.703193 0.659717 0.659717
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7762142050362102, 'f1': [0.7626051381089116, 0.8193172070681077, 0.782631463877425, 0.8980891719745221, 0.7044101270853962], 'avgF1': 0.7934106216228726, 'precision': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7762142050362102, 'recall': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7762142050362102, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgAccuracy': 0.7451398578167564, 'f1': [0.7499080499966836, 0.7369089365728758, 0.7980989394769558, 0.8802588996763754, 0.6922203519024327], 'avgF1': 0.7714790355250647, 'precision': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgPrecision': 0.7451398578167564, 'recall': [0.7413793103448276, 0.7126436781609196, 0.7976878612716763, 0.7861271676300579, 0.6878612716763006], 'avgRecall': 0.7451398578167564, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgAccuracy': 0.65280047837353, 'f1': [0.666958193221306, 0.7005450064667237, 0.7575712193301322, 0.6536964980544747, 0.7031353887503986], 'avgF1': 0.6963812611646071, 'precision': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgPrecision': 0.65280047837353, 'recall': [0.6551724137931034, 0.6724137931034483, 0.7572254335260116, 0.48554913294797686, 0.6936416184971098], 'avgRecall': 0.65280047837353, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgAccuracy': 0.7161716829446548, 'f1': [0.7258161950414926, 0.7983394145582627, 0.7911378573125346, 0.7859649122807019, 0.6440183805534138], 'avgF1': 0.7490553519492811, 'precision': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgPrecision': 0.7161716829446548, 'recall': [0.7183908045977011, 0.7931034482758621, 0.791907514450867, 0.6473988439306358, 0.630057803468208], 'avgRecall': 0.7161716829446548, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgAccuracy': 0.7473855557770248, 'f1': [0.7356183742329876, 0.7886998059411853, 0.7441433449703351, 0.9015873015873017, 0.6643998123346705], 'avgF1': 0.766889727813296, 'precision': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgPrecision': 0.7473855557770248, 'recall': [0.7298850574712644, 0.7816091954022989, 0.7456647398843931, 0.8208092485549133, 0.6589595375722543], 'avgRecall': 0.7473855557770248, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5557504484751844, 'f1': [0.6355735479569788, 0.6798662051724348, 0.7352264963289916, 0.18848167539267016, 0.6773916573765312], 'avgF1': 0.5833079164455213, 'precision': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5557504484751844, 'recall': [0.6264367816091954, 0.6494252873563219, 0.7341040462427746, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5557504484751844, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgAccuracy': 0.659710318251279, 'f1': [0.6837098692033294, 0.7053380089616209, 0.7693804268948776, 0.6536964980544747, 0.7016031031087794], 'avgF1': 0.7027455812446164, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgPrecision': 0.659710318251279, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7687861271676301, 0.48554913294797686, 0.6936416184971098], 'avgRecall': 0.659710318251279, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgAccuracy': 0.7762142050362102, 'f1': [0.7626051381089116, 0.8193172070681077, 0.782631463877425, 0.8980891719745221, 0.7044101270853962], 'avgF1': 0.7934106216228726, 'precision': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgPrecision': 0.7762142050362102, 'recall': [0.7586206896551724, 0.8160919540229885, 0.7861271676300579, 0.815028901734104, 0.7052023121387283], 'avgRecall': 0.7762142050362102, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.776214 0.793411 0.776214 0.776214
1 0.745140 0.771479 0.745140 0.745140
2 0.652800 0.696381 0.652800 0.652800
3 0.589011 0.538441 0.589011 0.589011
4 0.716172 0.749055 0.716172 0.716172
5 0.747386 0.766890 0.747386 0.747386
6 0.555750 0.583308 0.555750 0.555750
7 0.659710 0.702746 0.659710 0.659710
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7808251943392466, 'f1': [0.7573624842197081, 0.8381601879214974, 0.7763629151082398, 0.9050632911392403, 0.707684646871162], 'avgF1': 0.7969267050519695, 'precision': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7808251943392466, 'recall': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7808251943392466, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgAccuracy': 0.735884658826656, 'f1': [0.7441996594295445, 0.7470667263770712, 0.7747349079355358, 0.8655737704918033, 0.687152367430625], 'avgF1': 0.763745486332916, 'precision': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgPrecision': 0.735884658826656, 'recall': [0.735632183908046, 0.7241379310344828, 0.7745664739884393, 0.7630057803468208, 0.6820809248554913], 'avgRecall': 0.735884658826656, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgAccuracy': 0.6504551192611787, 'f1': [0.6726119698771305, 0.7212910961201756, 0.73448276402824, 0.6215139442231076, 0.7188901393080636], 'avgF1': 0.6937579827113435, 'precision': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgPrecision': 0.6504551192611787, 'recall': [0.6609195402298851, 0.6954022988505747, 0.7341040462427746, 0.4508670520231214, 0.7109826589595376], 'avgRecall': 0.6504551192611787, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgAccuracy': 0.7011294930569397, 'f1': [0.7540693402762367, 0.7877939851641717, 0.7612913297585413, 0.7816901408450704, 0.5944891736773938], 'avgF1': 0.7358667939442828, 'precision': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgPrecision': 0.7011294930569397, 'recall': [0.7471264367816092, 0.7758620689655172, 0.7630057803468208, 0.6416184971098265, 0.5780346820809249], 'avgRecall': 0.7011294930569397, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgAccuracy': 0.7439505680685669, 'f1': [0.7545617816091953, 0.7526797117314359, 0.7434873322446296, 0.9085173501577286, 0.6678223223286411], 'avgF1': 0.7654136996143261, 'precision': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgPrecision': 0.7439505680685669, 'recall': [0.7471264367816092, 0.735632183908046, 0.7456647398843931, 0.8323699421965318, 0.6589595375722543], 'avgRecall': 0.7439505680685669, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgAccuracy': 0.5626204238921002, 'f1': [0.6774410774410775, 0.6956140350877194, 0.7237720253553377, 0.18848167539267016, 0.6665109396848238], 'avgF1': 0.5903639505923257, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgPrecision': 0.5626204238921002, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7225433526011561, 0.10404624277456648, 0.653179190751445], 'avgRecall': 0.5626204238921002, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgAccuracy': 0.6585409607335061, 'f1': [0.6782407407407407, 0.7209330675066161, 0.7578494482396217, 0.6431372549019608, 0.707645744880386], 'avgF1': 0.701561251253865, 'precision': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgPrecision': 0.6585409607335061, 'recall': [0.6666666666666666, 0.6954022988505747, 0.7572254335260116, 0.47398843930635837, 0.6994219653179191], 'avgRecall': 0.6585409607335061, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgAccuracy': 0.7808251943392466, 'f1': [0.7573624842197081, 0.8381601879214974, 0.7763629151082398, 0.9050632911392403, 0.707684646871162], 'avgF1': 0.7969267050519695, 'precision': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgPrecision': 0.7808251943392466, 'recall': [0.7528735632183908, 0.8333333333333334, 0.7803468208092486, 0.8265895953757225, 0.7109826589595376], 'avgRecall': 0.7808251943392466, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.780825 0.796927 0.780825 0.780825
1 0.735885 0.763745 0.735885 0.735885
2 0.650455 0.693758 0.650455 0.650455
3 0.589011 0.538441 0.589011 0.589011
4 0.701129 0.735867 0.701129 0.701129
5 0.743951 0.765414 0.743951 0.743951
6 0.562620 0.590364 0.562620 0.562620
7 0.658541 0.701561 0.658541 0.658541
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.7819812637034084, 'f1': [0.7626051381089116, 0.8319495121318856, 0.7708818132762049, 0.9085173501577286, 0.7160018868075376], 'avgF1': 0.7979911400964537, 'precision': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.7819812637034084, 'recall': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.7819812637034084, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgAccuracy': 0.7370473722676234, 'f1': [0.7387928522187587, 0.7470667263770712, 0.7747349079355358, 0.8692810457516339, 0.6922203519024327], 'avgF1': 0.7644191768370865, 'precision': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgPrecision': 0.7370473722676234, 'recall': [0.7298850574712644, 0.7241379310344828, 0.7745664739884393, 0.7687861271676301, 0.6878612716763006], 'avgRecall': 0.7370473722676234, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgAccuracy': 0.6504750514915952, 'f1': [0.666958193221306, 0.710773778992635, 0.7460269916791861, 0.6215139442231076, 0.7248777846781], 'avgF1': 0.694030138558867, 'precision': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgPrecision': 0.6504750514915952, 'recall': [0.6551724137931034, 0.6839080459770115, 0.7456647398843931, 0.4508670520231214, 0.7167630057803468], 'avgRecall': 0.6504750514915952, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgAccuracy': 0.698804066175005, 'f1': [0.7545617816091953, 0.7975498607036771, 0.767403040882123, 0.7686832740213524, 0.5827172687489401], 'avgF1': 0.7341830451930575, 'precision': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgPrecision': 0.698804066175005, 'recall': [0.7471264367816092, 0.7873563218390804, 0.7687861271676301, 0.6242774566473989, 0.5664739884393064], 'avgRecall': 0.698804066175005, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgAccuracy': 0.7381901534781742, 'f1': [0.7205333412229964, 0.7701666995393626, 0.7331205954549055, 0.9085173501577286, 0.6656609537735448], 'avgF1': 0.7595997880297076, 'precision': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgPrecision': 0.7381901534781742, 'recall': [0.7126436781609196, 0.7528735632183908, 0.7341040462427746, 0.8323699421965318, 0.6589595375722543], 'avgRecall': 0.7381901534781742, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5660886319845857, 'f1': [0.6774410774410775, 0.6956140350877194, 0.7295077122643383, 0.18848167539267016, 0.6776272416953296], 'avgF1': 0.593734348376227, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5660886319845857, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7283236994219653, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5660886319845857, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgAccuracy': 0.6562421101587934, 'f1': [0.6782407407407407, 0.7104022398653563, 0.763487329101577, 0.626984126984127, 0.7188901393080636], 'avgF1': 0.6996009151999729, 'precision': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgPrecision': 0.6562421101587934, 'recall': [0.6666666666666666, 0.6839080459770115, 0.7630057803468208, 0.45664739884393063, 0.7109826589595376], 'avgRecall': 0.6562421101587934, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgAccuracy': 0.7819812637034084, 'f1': [0.7626051381089116, 0.8319495121318856, 0.7708818132762049, 0.9085173501577286, 0.7160018868075376], 'avgF1': 0.7979911400964537, 'precision': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgPrecision': 0.7819812637034084, 'recall': [0.7586206896551724, 0.8275862068965517, 0.7745664739884393, 0.8323699421965318, 0.7167630057803468], 'avgRecall': 0.7819812637034084, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.781981 0.797991 0.781981 0.781981
1 0.737047 0.764419 0.737047 0.737047
2 0.650475 0.694030 0.650475 0.650475
3 0.589011 0.538441 0.589011 0.589011
4 0.698804 0.734183 0.698804 0.698804
5 0.738190 0.759600 0.738190 0.738190
6 0.566089 0.593734 0.566089 0.566089
7 0.656242 0.699601 0.656242 0.656242
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgAccuracy': 0.732423094810976, 'f1': [0.7157671562434775, 0.767236450385442, 0.764010094465016, 0.8543046357615894, 0.7100861086068835], 'avgF1': 0.7622808890924817, 'precision': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgPrecision': 0.732423094810976, 'recall': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgRecall': 0.732423094810976, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgAccuracy': 0.6921267689854494, 'f1': [0.6612784074000162, 0.690126075975465, 0.7410180223807494, 0.8466666666666667, 0.688516082984237], 'avgF1': 0.7255210510814268, 'precision': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgPrecision': 0.6921267689854494, 'recall': [0.6494252873563219, 0.6609195402298851, 0.7398843930635838, 0.7341040462427746, 0.6763005780346821], 'avgRecall': 0.6921267689854494, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 16, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6366553717360972, 'f1': [0.6440729130384304, 0.6903623951667812, 0.7176240538965356, 0.6589147286821705, 0.6925765699788141], 'avgF1': 0.6807101321525464, 'precision': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6366553717360972, 'recall': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6366553717360972, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgAccuracy': 0.6931632449671118, 'f1': [0.7060784028789387, 0.7397835063050998, 0.7698100211294482, 0.8027681660899654, 0.6275255539756237], 'avgF1': 0.7291931300758152, 'precision': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgPrecision': 0.6931632449671118, 'recall': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6127167630057804], 'avgRecall': 0.6931632449671118, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgAccuracy': 0.6886386286625473, 'f1': [0.6894272677690964, 0.6796218751610743, 0.7059513050273538, 0.858085808580858, 0.6719611860392657], 'avgF1': 0.7210094885155296, 'precision': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgPrecision': 0.6886386286625473, 'recall': [0.6781609195402298, 0.6494252873563219, 0.7052023121387283, 0.7514450867052023, 0.6589595375722543], 'avgRecall': 0.6886386286625473, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.5603215733173875, 'f1': [0.6605387426298953, 0.7008436261117909, 0.7119772530481384, 0.18848167539267016, 0.6766345057538314], 'avgF1': 0.5876951605872652, 'precision': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.5603215733173875, 'recall': [0.6494252873563219, 0.6724137931034483, 0.7109826589595376, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.5603215733173875, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgAccuracy': 0.6412730051159391, 'f1': [0.6387204866421128, 0.7008436261117909, 0.7234981629262128, 0.664092664092664, 0.6971815732831559], 'avgF1': 0.6848673026111872, 'precision': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgPrecision': 0.6412730051159391, 'recall': [0.6264367816091954, 0.6724137931034483, 0.7225433526011561, 0.49710982658959535, 0.6878612716763006], 'avgRecall': 0.6412730051159391, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgAccuracy': 0.732423094810976, 'f1': [0.7157671562434775, 0.767236450385442, 0.764010094465016, 0.8543046357615894, 0.7100861086068835], 'avgF1': 0.7622808890924817, 'precision': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgPrecision': 0.732423094810976, 'recall': [0.7068965517241379, 0.7471264367816092, 0.7630057803468208, 0.7456647398843931, 0.6994219653179191], 'avgRecall': 0.732423094810976, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.732423 0.762281 0.732423 0.732423
1 0.692127 0.725521 0.692127 0.692127
2 0.636655 0.680710 0.636655 0.636655
3 0.589011 0.538441 0.589011 0.589011
4 0.693163 0.729193 0.693163 0.693163
5 0.688639 0.721009 0.688639 0.688639
6 0.560322 0.587695 0.560322 0.560322
7 0.641273 0.684867 0.641273 0.641273
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgAccuracy': 0.7266626802205833, 'f1': [0.7099366509926854, 0.7571732652192422, 0.758206208774358, 0.8543046357615894, 0.7047170545733049], 'avgF1': 0.756867563064236, 'precision': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgPrecision': 0.7266626802205833, 'recall': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgRecall': 0.7266626802205833, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgAccuracy': 0.6932695501960003, 'f1': [0.6615140705509314, 0.7007868423511822, 0.7467383877929485, 0.8310810810810811, 0.6955185553773727], 'avgF1': 0.7271277874307032, 'precision': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgPrecision': 0.6932695501960003, 'recall': [0.6494252873563219, 0.6724137931034483, 0.7456647398843931, 0.7109826589595376, 0.6878612716763006], 'avgRecall': 0.6932695501960003, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 14, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6366553717360972, 'f1': [0.6440729130384304, 0.6903623951667812, 0.7176240538965356, 0.6589147286821705, 0.693122877416869], 'avgF1': 0.6808193936401573, 'precision': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6366553717360972, 'recall': [0.632183908045977, 0.6609195402298851, 0.7167630057803468, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6366553717360972, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgAccuracy': 0.6943193143312737, 'f1': [0.7060784028789387, 0.7397835063050998, 0.7698100211294482, 0.8027681660899654, 0.6321668489298549], 'avgF1': 0.7301213890666614, 'precision': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgPrecision': 0.6943193143312737, 'recall': [0.6954022988505747, 0.7183908045977011, 0.7687861271676301, 0.6705202312138728, 0.6184971098265896], 'avgRecall': 0.6943193143312737, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgAccuracy': 0.6955551126171019, 'f1': [0.67280425980863, 0.7112402284816078, 0.7574038965192762, 0.815068493150685, 0.6996405085919428], 'avgF1': 0.7312314773104284, 'precision': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgPrecision': 0.6955551126171019, 'recall': [0.6609195402298851, 0.6839080459770115, 0.7572254335260116, 0.6878612716763006, 0.6878612716763006], 'avgRecall': 0.6955551126171019, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgAccuracy': 0.560328217394193, 'f1': [0.6547294961541786, 0.7008585851611275, 0.7178320767658422, 0.18848167539267016, 0.6776272416953296], 'avgF1': 0.5879058150338297, 'precision': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgPrecision': 0.560328217394193, 'recall': [0.6436781609195402, 0.6724137931034483, 0.7167630057803468, 0.10404624277456648, 0.6647398843930635], 'avgRecall': 0.560328217394193, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgAccuracy': 0.637798152946648, 'f1': [0.6387204866421128, 0.7060520587164044, 0.7176240538965356, 0.6536964980544747, 0.693122877416869], 'avgF1': 0.6818431949452793, 'precision': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgPrecision': 0.637798152946648, 'recall': [0.6264367816091954, 0.6781609195402298, 0.7167630057803468, 0.48554913294797686, 0.6820809248554913], 'avgRecall': 0.637798152946648, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgAccuracy': 0.7266626802205833, 'f1': [0.7099366509926854, 0.7571732652192422, 0.758206208774358, 0.8543046357615894, 0.7047170545733049], 'avgF1': 0.756867563064236, 'precision': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgPrecision': 0.7266626802205833, 'recall': [0.7011494252873564, 0.735632183908046, 0.7572254335260116, 0.7456647398843931, 0.6936416184971098], 'avgRecall': 0.7266626802205833, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.726663 0.756868 0.726663 0.726663
1 0.693270 0.727128 0.693270 0.693270
2 0.636655 0.680819 0.636655 0.636655
3 0.589011 0.538441 0.589011 0.589011
4 0.694319 0.730121 0.694319 0.694319
5 0.695555 0.731231 0.695555 0.695555
6 0.560328 0.587906 0.560328 0.560328
7 0.637798 0.681843 0.637798 0.637798
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgAccuracy': 0.7220516909175471, 'f1': [0.6939488886435876, 0.7622097742380217, 0.758206208774358, 0.8543046357615894, 0.6939330473089527], 'avgF1': 0.7525205109453019, 'precision': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgPrecision': 0.7220516909175471, 'recall': [0.6839080459770115, 0.7413793103448276, 0.7572254335260116, 0.7456647398843931, 0.6820809248554913], 'avgRecall': 0.7220516909175471, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgAccuracy': 0.7175137864593715, 'f1': [0.6802616577889917, 0.7059695958472377, 0.7525283324971606, 0.9015873015873017, 0.6776272416953296], 'avgF1': 0.7435948258832042, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgPrecision': 0.7175137864593715, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgRecall': 0.7175137864593715, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgAccuracy': 0.5973224370473723, 'f1': [0.6440729130384304, 0.7112402284816078, 0.7237553608055194, 0.4200913242009132, 0.6939330473089527], 'avgF1': 0.6386185747670847, 'precision': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgPrecision': 0.5973224370473723, 'recall': [0.632183908045977, 0.6839080459770115, 0.7225433526011561, 0.2658959537572254, 0.6820809248554913], 'avgRecall': 0.5973224370473723, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgAccuracy': 0.6977941665005647, 'f1': [0.7060784028789387, 0.7340820264186416, 0.7698100211294482, 0.8191126279863481, 0.6321668489298549], 'avgF1': 0.7322499854686463, 'precision': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgPrecision': 0.6977941665005647, 'recall': [0.6954022988505747, 0.7126436781609196, 0.7687861271676301, 0.6936416184971098, 0.6184971098265896], 'avgRecall': 0.6977941665005647, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgAccuracy': 0.6920935486014218, 'f1': [0.639530116738321, 0.7372040475488753, 0.7402494675996348, 0.8350168350168351, 0.6773916573765312], 'avgF1': 0.7258784248560395, 'precision': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgPrecision': 0.6920935486014218, 'recall': [0.6264367816091954, 0.7126436781609196, 0.7398843930635838, 0.7167630057803468, 0.6647398843930635], 'avgRecall': 0.6920935486014218, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgAccuracy': 0.5545810909574115, 'f1': [0.6423519009725907, 0.6850878202274172, 0.7294153169029419, 0.18848167539267016, 0.6665109396848238], 'avgF1': 0.5823695306360888, 'precision': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgPrecision': 0.5545810909574115, 'recall': [0.632183908045977, 0.6551724137931034, 0.7283236994219653, 0.10404624277456648, 0.653179190751445], 'avgRecall': 0.5545810909574115, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgAccuracy': 0.6470467078599429, 'f1': [0.6329501915708813, 0.7112402284816078, 0.7295277038428584, 0.6743295019157087, 0.704282045510801], 'avgF1': 0.6904659342643714, 'precision': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgPrecision': 0.6470467078599429, 'recall': [0.6206896551724138, 0.6839080459770115, 0.7283236994219653, 0.5086705202312138, 0.6936416184971098], 'avgRecall': 0.6470467078599429, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgAccuracy': 0.7175137864593715, 'f1': [0.6802616577889917, 0.7059695958472377, 0.7525283324971606, 0.9015873015873017, 0.6776272416953296], 'avgF1': 0.7435948258832042, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgPrecision': 0.7175137864593715, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.8208092485549133, 0.6647398843930635], 'avgRecall': 0.7175137864593715, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.722052 0.752521 0.722052 0.722052
1 0.717514 0.743595 0.717514 0.717514
2 0.597322 0.638619 0.597322 0.597322
3 0.589011 0.538441 0.589011 0.589011
4 0.697794 0.732250 0.697794 0.697794
5 0.692094 0.725878 0.692094 0.692094
6 0.554581 0.582370 0.554581 0.554581
7 0.647047 0.690466 0.647047 0.647047
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgAccuracy': 0.6723672845658096, 'f1': [0.6885908897403151, 0.7466155810983398, 0.7465399826823617, 0.6992481203007519, 0.6887435437058355], 'avgF1': 0.7139476235055208, 'precision': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgPrecision': 0.6723672845658096, 'recall': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6763005780346821], 'avgRecall': 0.6723672845658096, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgAccuracy': 0.7302039731579297, 'f1': [0.7060445027907718, 0.7060819655455894, 0.7408661929482224, 0.9015873015873017, 0.6864138286685275], 'avgF1': 0.7481987583080826, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgPrecision': 0.7302039731579297, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgRecall': 0.7302039731579297, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgAccuracy': 0.5927247358979469, 'f1': [0.6377432198933213, 0.6955848928865033, 0.7178320767658422, 0.4128440366972477, 0.7047170545733049], 'avgF1': 0.6337442561632438, 'precision': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgPrecision': 0.5927247358979469, 'recall': [0.6264367816091954, 0.6666666666666666, 0.7167630057803468, 0.26011560693641617, 0.6936416184971098], 'avgRecall': 0.5927247358979469, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgAccuracy': 0.6469337585542488, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6536964980544747, 0.5772928193873451], 'avgF1': 0.6896540541319812, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgPrecision': 0.6469337585542488, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgRecall': 0.6469337585542488, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgAccuracy': 0.6539233273536642, 'f1': [0.6783424908424908, 0.7165501994765329, 0.7409295587368592, 0.6589147286821705, 0.694201105629824], 'avgF1': 0.6977876166735755, 'precision': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgPrecision': 0.6539233273536642, 'recall': [0.6666666666666666, 0.6896551724137931, 0.7398843930635838, 0.4913294797687861, 0.6820809248554913], 'avgRecall': 0.6539233273536642, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgAccuracy': 0.5361371337452661, 'f1': [0.6199988947833777, 0.6634273772204807, 0.7064515809198981, 0.18848167539267016, 0.644309926201206], 'avgF1': 0.5645338909035266, 'precision': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgPrecision': 0.5361371337452661, 'recall': [0.6091954022988506, 0.632183908045977, 0.7052023121387283, 0.10404624277456648, 0.630057803468208], 'avgRecall': 0.5361371337452661, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgAccuracy': 0.5961597236064049, 'f1': [0.643017960828128, 0.7158616514987058, 0.7119772530481384, 0.40552995391705066, 0.7047170545733049], 'avgF1': 0.6362207747730656, 'precision': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgPrecision': 0.5961597236064049, 'recall': [0.632183908045977, 0.6896551724137931, 0.7109826589595376, 0.2543352601156069, 0.6936416184971098], 'avgRecall': 0.5961597236064049, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgAccuracy': 0.7302039731579297, 'f1': [0.7060445027907718, 0.7060819655455894, 0.7408661929482224, 0.9015873015873017, 0.6864138286685275], 'avgF1': 0.7481987583080826, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgPrecision': 0.7302039731579297, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7398843930635838, 0.8208092485549133, 0.7167630057803468], 'avgRecall': 0.7302039731579297, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.672367 0.713948 0.672367 0.672367
1 0.730204 0.748199 0.730204 0.730204
2 0.592725 0.633744 0.592725 0.592725
3 0.589011 0.538441 0.589011 0.589011
4 0.646934 0.689654 0.646934 0.646934
5 0.653923 0.697788 0.653923 0.653923
6 0.536137 0.564534 0.536137 0.536137
7 0.596160 0.636221 0.596160 0.596160
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgAccuracy': 0.672360640489004, 'f1': [0.6943320611070581, 0.7466155810983398, 0.7408661929482224, 0.6992481203007519, 0.6887435437058355], 'avgF1': 0.7139610998320416, 'precision': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgPrecision': 0.672360640489004, 'recall': [0.6839080459770115, 0.7241379310344828, 0.7398843930635838, 0.5375722543352601, 0.6763005780346821], 'avgRecall': 0.672360640489004, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgAccuracy': 0.7244236263371204, 'f1': [0.7059289222790964, 0.7060819655455894, 0.746692218715994, 0.9050632911392403, 0.688516082984237], 'avgF1': 0.7504564961328315, 'precision': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgPrecision': 0.7244236263371204, 'recall': [0.6954022988505747, 0.6781609195402298, 0.7456647398843931, 0.8265895953757225, 0.6763005780346821], 'avgRecall': 0.7244236263371204, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgAccuracy': 0.5892565278054614, 'f1': [0.625947848405732, 0.7061101028433151, 0.7178320767658422, 0.40552995391705066, 0.6939330473089527], 'avgF1': 0.6298706058481786, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgPrecision': 0.5892565278054614, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgRecall': 0.5892565278054614, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgAccuracy': 0.6469337585542488, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6536964980544747, 0.5772928193873451], 'avgF1': 0.6896540541319812, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgPrecision': 0.6469337585542488, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.48554913294797686, 0.5664739884393064], 'avgRecall': 0.6469337585542488, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgAccuracy': 0.6504617633379841, 'f1': [0.6837348786775187, 0.7053380089616209, 0.7523832510394124, 0.626984126984127, 0.7050627546795359], 'avgF1': 0.694700604068443, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgPrecision': 0.6504617633379841, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgRecall': 0.6504617633379841, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgAccuracy': 0.5395588333001129, 'f1': [0.6140143487465257, 0.7061101028433151, 0.6946869653981668, 0.18848167539267016, 0.6329503615101394], 'avgF1': 0.5672486907781634, 'precision': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgPrecision': 0.5395588333001129, 'recall': [0.603448275862069, 0.6781609195402298, 0.6936416184971098, 0.10404624277456648, 0.6184971098265896], 'avgRecall': 0.5395588333001129, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgAccuracy': 0.5961663676832104, 'f1': [0.6318622721040069, 0.7215593919778308, 0.7232565122738532, 0.39069767441860465, 0.7100861086068835], 'avgF1': 0.6354923918762359, 'precision': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgPrecision': 0.5961663676832104, 'recall': [0.6206896551724138, 0.6954022988505747, 0.7225433526011561, 0.24277456647398843, 0.6994219653179191], 'avgRecall': 0.5961663676832104, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgAccuracy': 0.6504617633379841, 'f1': [0.6837348786775187, 0.7053380089616209, 0.7523832510394124, 0.626984126984127, 0.7050627546795359], 'avgF1': 0.694700604068443, 'precision': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgPrecision': 0.6504617633379841, 'recall': [0.6724137931034483, 0.6781609195402298, 0.7514450867052023, 0.45664739884393063, 0.6936416184971098], 'avgRecall': 0.6504617633379841, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.672361 0.713961 0.672361 0.672361
1 0.724424 0.750456 0.724424 0.724424
2 0.589257 0.629871 0.589257 0.589257
3 0.589011 0.538441 0.589011 0.589011
4 0.646934 0.689654 0.646934 0.646934
5 0.650462 0.694701 0.650462 0.650462
6 0.539559 0.567249 0.539559 0.539559
7 0.596166 0.635492 0.596166 0.596166
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgAccuracy': 0.6712112152016477, 'f1': [0.6889352784899223, 0.7466155810983398, 0.746692218715994, 0.6992481203007519, 0.6832668243401608], 'avgF1': 0.7129516045890337, 'precision': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgPrecision': 0.6712112152016477, 'recall': [0.6781609195402298, 0.7241379310344828, 0.7456647398843931, 0.5375722543352601, 0.6705202312138728], 'avgRecall': 0.6712112152016477, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgAccuracy': 0.7267224769118331, 'f1': [0.7059289222790964, 0.7165501994765329, 0.7410371632538006, 0.9050632911392403, 0.694201105629824], 'avgF1': 0.7525561363556988, 'precision': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgPrecision': 0.7267224769118331, 'recall': [0.6954022988505747, 0.6896551724137931, 0.7398843930635838, 0.8265895953757225, 0.6820809248554913], 'avgRecall': 0.7267224769118331, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgAccuracy': 0.5858082519433925, 'f1': [0.6191933347117247, 0.6956140350877194, 0.7178320767658422, 0.40552995391705066, 0.694201105629824], 'avgF1': 0.6264741012224322, 'precision': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgPrecision': 0.5858082519433925, 'recall': [0.6091954022988506, 0.6666666666666666, 0.7167630057803468, 0.2543352601156069, 0.6820809248554913], 'avgRecall': 0.5858082519433925, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgAccuracy': 0.6515580360108962, 'f1': [0.7060784028789387, 0.729883030266172, 0.7813195200729757, 0.6743295019157087, 0.5772928193873451], 'avgF1': 0.693780654904228, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgPrecision': 0.6515580360108962, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7803468208092486, 0.5086705202312138, 0.5664739884393064], 'avgRecall': 0.6515580360108962, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgAccuracy': 0.6527739020663079, 'f1': [0.6672508525956802, 0.7209330675066161, 0.7122625264118102, 0.7041198501872659, 0.6721740443329903], 'avgF1': 0.6953480682068726, 'precision': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgPrecision': 0.6527739020663079, 'recall': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgRecall': 0.6527739020663079, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgAccuracy': 0.5430270413925985, 'f1': [0.6199988947833777, 0.7008585851611275, 0.6949398782108746, 0.18848167539267016, 0.6497628343352881], 'avgF1': 0.5708083735766676, 'precision': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgPrecision': 0.5430270413925985, 'recall': [0.6091954022988506, 0.6724137931034483, 0.6936416184971098, 0.10404624277456648, 0.6358381502890174], 'avgRecall': 0.5430270413925985, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgAccuracy': 0.5915686665337851, 'f1': [0.6252023386379308, 0.7059056678557273, 0.7119772530481384, 0.4200913242009132, 0.6996405085919428], 'avgF1': 0.6325634184669305, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgPrecision': 0.5915686665337851, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7109826589595376, 0.2658959537572254, 0.6878612716763006], 'avgRecall': 0.5915686665337851, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgAccuracy': 0.6527739020663079, 'f1': [0.6672508525956802, 0.7209330675066161, 0.7122625264118102, 0.7041198501872659, 0.6721740443329903], 'avgF1': 0.6953480682068726, 'precision': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgPrecision': 0.6527739020663079, 'recall': [0.6551724137931034, 0.6954022988505747, 0.7109826589595376, 0.5433526011560693, 0.6589595375722543], 'avgRecall': 0.6527739020663079, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.671211 0.712952 0.671211 0.671211
1 0.726722 0.752556 0.726722 0.726722
2 0.585808 0.626474 0.585808 0.585808
3 0.589011 0.538441 0.589011 0.589011
4 0.651558 0.693781 0.651558 0.651558
5 0.652774 0.695348 0.652774 0.652774
6 0.543027 0.570808 0.543027 0.543027
7 0.591569 0.632563 0.591569 0.591569
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgAccuracy': 0.6723672845658096, 'f1': [0.6934743841841423, 0.7404758526086751, 0.758206208774358, 0.6893939393939393, 0.6887435437058355], 'avgF1': 0.71405878573339, 'precision': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgPrecision': 0.6723672845658096, 'recall': [0.6839080459770115, 0.7183908045977011, 0.7572254335260116, 0.5260115606936416, 0.6763005780346821], 'avgRecall': 0.6723672845658096, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgAccuracy': 0.7198192811108897, 'f1': [0.6782608695652173, 0.7158616514987058, 0.7583005221859206, 0.8945686900958467, 0.6888813328799728], 'avgF1': 0.7471746132451327, 'precision': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgPrecision': 0.7198192811108897, 'recall': [0.6666666666666666, 0.6896551724137931, 0.7572254335260116, 0.8092485549132948, 0.6763005780346821], 'avgRecall': 0.7198192811108897, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgAccuracy': 0.5800079728921665, 'f1': [0.6252023386379308, 0.7060520587164044, 0.7058013118092785, 0.38317757009345793, 0.6777699519114003], 'avgF1': 0.6196006462336944, 'precision': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgPrecision': 0.5800079728921665, 'recall': [0.6149425287356322, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6647398843930635], 'avgRecall': 0.5800079728921665, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgAccuracy': 0.6816091954022988, 'f1': [0.711544227886057, 0.729883030266172, 0.7755655414866272, 0.6793893129770993, 0.7216046638011956], 'avgF1': 0.7235973552834302, 'precision': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgPrecision': 0.6816091954022988, 'recall': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgRecall': 0.6816091954022988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6828197573215363, 0.729883030266172, 0.746791023242393, 0.664092664092664, 0.7111040948171177], 'avgF1': 0.7069381139479766, 'precision': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgPrecision': 0.6643013753238988, 'recall': [0.6724137931034483, 0.7068965517241379, 0.7456647398843931, 0.49710982658959535, 0.6994219653179191], 'avgRecall': 0.6643013753238988, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgAccuracy': 0.5441897548335659, 'f1': [0.6172885281771698, 0.6956140350877194, 0.7006362584825384, 0.18848167539267016, 0.6551957941458886], 'avgF1': 0.5714432582571972, 'precision': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgPrecision': 0.5441897548335659, 'recall': [0.6091954022988506, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6416184971098265], 'avgRecall': 0.5441897548335659, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgAccuracy': 0.5903793767855956, 'f1': [0.6363903285293359, 0.7215593919778308, 0.7169746279190063, 0.39069767441860465, 0.6832668243401608], 'avgF1': 0.6297777694369877, 'precision': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgPrecision': 0.5903793767855956, 'recall': [0.6264367816091954, 0.6954022988505747, 0.7167630057803468, 0.24277456647398843, 0.6705202312138728], 'avgRecall': 0.5903793767855956, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgAccuracy': 0.6816091954022988, 'f1': [0.711544227886057, 0.729883030266172, 0.7755655414866272, 0.6793893129770993, 0.7216046638011956], 'avgF1': 0.7235973552834302, 'precision': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgPrecision': 0.6816091954022988, 'recall': [0.7011494252873564, 0.7068965517241379, 0.7745664739884393, 0.5144508670520231, 0.7109826589595376], 'avgRecall': 0.6816091954022988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.672367 0.714059 0.672367 0.672367
1 0.719819 0.747175 0.719819 0.719819
2 0.580008 0.619601 0.580008 0.580008
3 0.589011 0.538441 0.589011 0.589011
4 0.681609 0.723597 0.681609 0.681609
5 0.664301 0.706938 0.664301 0.664301
6 0.544190 0.571443 0.544190 0.544190
7 0.590379 0.629778 0.590379 0.590379
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgAccuracy': 0.6689057205501295, 'f1': [0.6934743841841423, 0.7340820264186416, 0.764010094465016, 0.664092664092664, 0.6996405085919428], 'avgF1': 0.7110599355504813, 'precision': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgPrecision': 0.6689057205501295, 'recall': [0.6839080459770115, 0.7126436781609196, 0.7630057803468208, 0.49710982658959535, 0.6878612716763006], 'avgRecall': 0.6689057205501295, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgAccuracy': 0.7071290944123314, 'f1': [0.6783424908424908, 0.6951566951566953, 0.7583005221859206, 0.8802588996763754, 0.6722583732461128], 'avgF1': 0.736863396221519, 'precision': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgPrecision': 0.7071290944123314, 'recall': [0.6666666666666666, 0.6666666666666666, 0.7572254335260116, 0.7861271676300579, 0.6589595375722543], 'avgRecall': 0.7071290944123314, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgAccuracy': 0.5903660886319846, 'f1': [0.6605387426298953, 0.7110521992222772, 0.700194554963341, 0.37558685446009393, 0.6996405085919428], 'avgF1': 0.6294025719735101, 'precision': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgPrecision': 0.5903660886319846, 'recall': [0.6494252873563219, 0.6839080459770115, 0.6994219653179191, 0.23121387283236994, 0.6878612716763006], 'avgRecall': 0.5903660886319846, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgAccuracy': 0.6781476313866188, 'f1': [0.7060445027907718, 0.729883030266172, 0.7755655414866272, 0.6692307692307693, 0.7216046638011956], 'avgF1': 0.7204657015151071, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgPrecision': 0.6781476313866188, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgRecall': 0.6781476313866188, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgAccuracy': 0.650421898877151, 'f1': [0.6780891601923789, 0.7410728652814014, 0.7352815242988655, 0.6377952755905512, 0.6777699519114003], 'avgF1': 0.6940017554549195, 'precision': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgPrecision': 0.650421898877151, 'recall': [0.6666666666666666, 0.7183908045977011, 0.7341040462427746, 0.4682080924855491, 0.6647398843930635], 'avgRecall': 0.650421898877151, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgAccuracy': 0.5395588333001129, 'f1': [0.6243604263556551, 0.6955848928865033, 0.7006362584825384, 0.18848167539267016, 0.6272274267490533], 'avgF1': 0.567258135973284, 'precision': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgPrecision': 0.5395588333001129, 'recall': [0.6149425287356322, 0.6666666666666666, 0.6994219653179191, 0.10404624277456648, 0.6127167630057804], 'avgRecall': 0.5395588333001129, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgAccuracy': 0.5926782273603083, 'f1': [0.660035944822963, 0.7113403409850614, 0.7229385363772938, 0.37558685446009393, 0.6887435437058355], 'avgF1': 0.6317290440702495, 'precision': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgPrecision': 0.5926782273603083, 'recall': [0.6494252873563219, 0.6839080459770115, 0.7225433526011561, 0.23121387283236994, 0.6763005780346821], 'avgRecall': 0.5926782273603083, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgAccuracy': 0.6781476313866188, 'f1': [0.7060445027907718, 0.729883030266172, 0.7755655414866272, 0.6692307692307693, 0.7216046638011956], 'avgF1': 0.7204657015151071, 'precision': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgPrecision': 0.6781476313866188, 'recall': [0.6954022988505747, 0.7068965517241379, 0.7745664739884393, 0.5028901734104047, 0.7109826589595376], 'avgRecall': 0.6781476313866188, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.668906 0.711060 0.668906 0.668906
1 0.707129 0.736863 0.707129 0.707129
2 0.590366 0.629403 0.590366 0.590366
3 0.589011 0.538441 0.589011 0.589011
4 0.678148 0.720466 0.678148 0.678148
5 0.650422 0.694002 0.650422 0.650422
6 0.539559 0.567258 0.539559 0.539559
7 0.592678 0.631729 0.592678 0.592678
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgAccuracy': 0.6562221779283769, 'f1': [0.6726378568767298, 0.7314638951478758, 0.7352815242988655, 0.664092664092664, 0.6943802691001552], 'avgF1': 0.699571241903258, 'precision': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgPrecision': 0.6562221779283769, 'recall': [0.6609195402298851, 0.7068965517241379, 0.7341040462427746, 0.49710982658959535, 0.6820809248554913], 'avgRecall': 0.6562221779283769, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgAccuracy': 0.700225898611388, 'f1': [0.6435917379656038, 0.7003905678898892, 0.746791023242393, 0.8838709677419355, 0.6722583732461128], 'avgF1': 0.7293805340171868, 'precision': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgPrecision': 0.700225898611388, 'recall': [0.632183908045977, 0.6724137931034483, 0.7456647398843931, 0.791907514450867, 0.6589595375722543], 'avgRecall': 0.700225898611388, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgAccuracy': 0.5869377450003322, 'f1': [0.6423519009725907, 0.6954685099846389, 0.7104895226282509, 0.39069767441860465, 0.6943802691001552], 'avgF1': 0.626677575420848, 'precision': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgPrecision': 0.5869377450003322, 'recall': [0.632183908045977, 0.6666666666666666, 0.7109826589595376, 0.24277456647398843, 0.6820809248554913], 'avgRecall': 0.5869377450003322, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgAccuracy': 0.5890106969636569, 'f1': [0.6179526873886999, 0.7363619777412881, 0.533935969056559, 0.18848167539267016, 0.6154740548800743], 'avgF1': 0.5384412728918583, 'precision': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgPrecision': 0.5890106969636569, 'recall': [0.7011494252873564, 0.8045977011494253, 0.6242774566473989, 0.10404624277456648, 0.7109826589595376], 'avgRecall': 0.5890106969636569, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6431372549019608, 0.7218893598073546], 'avgF1': 0.7073939061143014, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgPrecision': 0.6643013753238988, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgRecall': 0.6643013753238988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgAccuracy': 0.6342834363165238, 'f1': [0.6616738617025865, 0.7217405838095492, 0.7059513050273538, 0.626984126984127, 0.6777699519114003], 'avgF1': 0.6788239658870033, 'precision': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgPrecision': 0.6342834363165238, 'recall': [0.6494252873563219, 0.6954022988505747, 0.7052023121387283, 0.45664739884393063, 0.6647398843930635], 'avgRecall': 0.6342834363165238, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgAccuracy': 0.5384559165503953, 'f1': [0.6111149863635583, 0.6630212769409226, 0.7121502485409023, 0.18848167539267016, 0.6555610784635982], 'avgF1': 0.5660658531403303, 'precision': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgPrecision': 0.5384559165503953, 'recall': [0.603448275862069, 0.632183908045977, 0.7109826589595376, 0.10404624277456648, 0.6416184971098265], 'avgRecall': 0.5384559165503953, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgAccuracy': 0.5869244568467211, 'f1': [0.6423519009725907, 0.7061101028433151, 0.700194554963341, 0.39069767441860465, 0.6943802691001552], 'avgF1': 0.6267469004596014, 'precision': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgPrecision': 0.5869244568467211, 'recall': [0.632183908045977, 0.6781609195402298, 0.6994219653179191, 0.24277456647398843, 0.6820809248554913], 'avgRecall': 0.5869244568467211, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgAccuracy': 0.6643013753238988, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6431372549019608, 0.7218893598073546], 'avgF1': 0.7073939061143014, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgPrecision': 0.6643013753238988, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.47398843930635837, 0.7109826589595376], 'avgRecall': 0.6643013753238988, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.656222 0.699571 0.656222 0.656222
1 0.700226 0.729381 0.700226 0.700226
2 0.586938 0.626678 0.586938 0.586938
3 0.589011 0.538441 0.589011 0.589011
4 0.664301 0.707394 0.664301 0.664301
5 0.634283 0.678824 0.634283 0.634283
6 0.538456 0.566066 0.538456 0.538456
7 0.586924 0.626747 0.586924 0.586924
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgAccuracy': 0.6562155338515713, 'f1': [0.6726378568767298, 0.7365278399761159, 0.7410371632538006, 0.6431372549019608, 0.7053210654251031], 'avgF1': 0.6997322360867421, 'precision': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgPrecision': 0.6562155338515713, 'recall': [0.6609195402298851, 0.7126436781609196, 0.7398843930635838, 0.47398843930635837, 0.6936416184971098], 'avgRecall': 0.6562155338515713, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgAccuracy': 0.7001926782273603, 'f1': [0.656151617887214, 0.7165501994765329, 0.7120659903583504, 0.8766233766233766, 0.6889309902629832], 'avgF1': 0.7300644349216914, 'precision': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgPrecision': 0.7001926782273603, 'recall': [0.6436781609195402, 0.6896551724137931, 0.7109826589595376, 0.7803468208092486, 0.6763005780346821], 'avgRecall': 0.7001926782273603, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgAccuracy': 0.5823201116204904, 'f1': [0.6363903285293359, 0.6954685099846389, 0.7049612756344981, 0.38317757009345793, 0.6888813328799728], 'avgF1': 0.6217758034243808, 'precision': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgPrecision': 0.5823201116204904, 'recall': [0.6264367816091954, 0.6666666666666666, 0.7052023121387283, 0.23699421965317918, 0.6763005780346821], 'avgRecall': 0.5823201116204904, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgAccuracy': 0.6690585343166567, 'f1': [0.609550894655765, 0.6955539179562761, 0.6892435285247549, 0.8729641693811074, 0.633339212558024], 'avgF1': 0.7001303446151854, 'precision': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgPrecision': 0.6690585343166567, 'recall': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgRecall': 0.6690585343166567, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgAccuracy': 0.6654574446880606, 'f1': [0.6782407407407407, 0.7354959663470932, 0.758206208774358, 0.6484375, 0.7218893598073546], 'avgF1': 0.7084539551339093, 'precision': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgPrecision': 0.6654574446880606, 'recall': [0.6666666666666666, 0.7126436781609196, 0.7572254335260116, 0.4797687861271676, 0.7109826589595376], 'avgRecall': 0.6654574446880606, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgAccuracy': 0.6389276460035878, 'f1': [0.6617128787851937, 0.7060520587164044, 0.7233783946779984, 0.6431372549019608, 0.6828651242491945], 'avgF1': 0.6834291422661504, 'precision': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgPrecision': 0.6389276460035878, 'recall': [0.6494252873563219, 0.6781609195402298, 0.7225433526011561, 0.47398843930635837, 0.6705202312138728], 'avgRecall': 0.6389276460035878, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgAccuracy': 0.5407082585874693, 'f1': [0.6252023386379308, 0.7007868423511822, 0.7121502485409023, 0.1693121693121693, 0.626829637946328], 'avgF1': 0.5668562473577025, 'precision': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgPrecision': 0.5407082585874693, 'recall': [0.6149425287356322, 0.6724137931034483, 0.7109826589595376, 0.09248554913294797, 0.6127167630057804], 'avgRecall': 0.5407082585874693, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgAccuracy': 0.5846256062720085, 'f1': [0.6303935307496151, 0.7061101028433151, 0.7049612756344981, 0.38317757009345793, 0.6943802691001552], 'avgF1': 0.6238045496842083, 'precision': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgPrecision': 0.5846256062720085, 'recall': [0.6206896551724138, 0.6781609195402298, 0.7052023121387283, 0.23699421965317918, 0.6820809248554913], 'avgRecall': 0.5846256062720085, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgAccuracy': 0.6690585343166567, 'f1': [0.609550894655765, 0.6955539179562761, 0.6892435285247549, 0.8729641693811074, 0.633339212558024], 'avgF1': 0.7001303446151854, 'precision': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgPrecision': 0.6690585343166567, 'recall': [0.5977011494252874, 0.6666666666666666, 0.6878612716763006, 0.7745664739884393, 0.6184971098265896], 'avgRecall': 0.6690585343166567, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.656216 0.699732 0.656216 0.656216
1 0.700193 0.730064 0.700193 0.700193
2 0.582320 0.621776 0.582320 0.582320
3 0.669059 0.700130 0.669059 0.669059
4 0.665457 0.708454 0.665457 0.665457
5 0.638928 0.683429 0.638928 0.638928
6 0.540708 0.566856 0.540708 0.540708
7 0.584626 0.623805 0.584626 0.584626
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))
Current date and time : 2021-06-05 10:17:02
# Original Dataset
X2 = pd.concat([X_train_ord, X_test_ord]) #.to_numpy()
y2 = pd.concat([y_train_ord, y_test_ord]).to_numpy()
#data2 = (X2, y2, n_folds)
print('********************************************')
print('Starting Original data set....')
print('********************************************')
for i in range(l ,6 , -1):
col = []
col = df[:i]
nX2 = X2.loc[:, col]
nX2 = nX2.to_numpy()
data2 = (nX2, y2, n_folds)
hyper_search(modelDictionary, modelParamsDictionary, data2, col)
********************************************
Starting Original data set....
********************************************
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgAccuracy': 0.749890988372093, 'f1': [0.7163066220090751, 0.7804492770684618, 0.745016611295681, 0.7577327500191879, 0.6551259410725903], 'avgF1': 0.7309262402929992, 'precision': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgPrecision': 0.749890988372093, 'recall': [0.7286821705426356, 0.7906976744186046, 0.7674418604651163, 0.7829457364341085, 0.6796875], 'avgRecall': 0.749890988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgAccuracy': 0.7608527131782946, 'f1': [0.6808189226793878, 0.7418047322288088, 0.7744338668752504, 0.7599524823681759, 0.7285067873303167], 'avgF1': 0.737103358296388, 'precision': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgPrecision': 0.7608527131782946, 'recall': [0.7131782945736435, 0.751937984496124, 0.7984496124031008, 0.7906976744186046, 0.75], 'avgRecall': 0.7608527131782946, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgAccuracy': 0.7623546511627907, 'f1': [0.6808189226793878, 0.7982676420278779, 0.7697812954980905, 0.6928223031968, 0.65], 'avgF1': 0.7183380326804313, 'precision': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgPrecision': 0.7623546511627907, 'recall': [0.7131782945736435, 0.8217054263565892, 0.8062015503875969, 0.751937984496124, 0.71875], 'avgRecall': 0.7623546511627907, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgAccuracy': 0.7484375, 'f1': [0.6098389982110913, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6744062389223681], 'avgF1': 0.6779174026907913, 'precision': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgPrecision': 0.7484375, 'recall': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgRecall': 0.7484375, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7592781007751938, 'f1': [0.6808189226793878, 0.7558764019683761, 0.7664579606440072, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7358921472980327, 'precision': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7592781007751938, 'recall': [0.7131782945736435, 0.7751937984496124, 0.7829457364341085, 0.7906976744186046, 0.734375], 'avgRecall': 0.7592781007751938, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgAccuracy': 0.7141957364341085, 'f1': [0.7379664683612764, 0.7356029920194277, 0.7196908945104614, 0.7130246958024337, 0.6627033792240301], 'avgF1': 0.7137976859835259, 'precision': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgPrecision': 0.7141957364341085, 'recall': [0.7364341085271318, 0.7286821705426356, 0.7286821705426356, 0.7209302325581395, 0.65625], 'avgRecall': 0.7141957364341085, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.677036383162856, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.6808189226793878, 0.780725697856389, 0.7697812954980905, 0.712020909247, 0.7003205128205128], 'avgF1': 0.728733467620276, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.6808189226793878, 0.780725697856389, 0.7697812954980905, 0.712020909247, 0.7003205128205128], 'avgF1': 0.728733467620276, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7674418604651163, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.749891 0.730926 0.749891 0.749891
1 0.760853 0.737103 0.760853 0.760853
2 0.762355 0.718338 0.762355 0.762355
3 0.748437 0.677917 0.748437 0.748437
4 0.759278 0.735892 0.759278 0.759278
5 0.714196 0.713798 0.714196 0.714196
6 0.753113 0.677036 0.753113 0.753113
7 0.765480 0.728733 0.765480 0.765480
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgAccuracy': 0.7514413759689923, 'f1': [0.722972409769109, 0.7868593361932715, 0.7602450484743948, 0.7446672012830794, 0.6551259410725903], 'avgF1': 0.733973987358489, 'precision': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgPrecision': 0.7514413759689923, 'recall': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7674418604651163, 0.6796875], 'avgRecall': 0.7514413759689923, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6808189226793878, 0.7479232440415672, 0.7853697315626679, 0.7710053875124555, 0.7285067873303167], 'avgF1': 0.7427248146252791, 'precision': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgAccuracy': 0.759265988372093, 'f1': [0.664364575992483, 0.7697812954980905, 0.7501835985312117, 0.6986158120124709, 0.6546732837055418], 'avgF1': 0.7075237131479596, 'precision': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgPrecision': 0.759265988372093, 'recall': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgRecall': 0.759265988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgAccuracy': 0.7484375, 'f1': [0.6098389982110913, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6744062389223681], 'avgF1': 0.6779174026907913, 'precision': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgPrecision': 0.7484375, 'recall': [0.689922480620155, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7421875], 'avgRecall': 0.7484375, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.7088378086789738, 0.7558764019683761, 0.77677987271754, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7435603069126564, 'precision': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgAccuracy': 0.704905523255814, 'f1': [0.683884521667255, 0.7148013182874647, 0.7332076984763432, 0.7034509662814625, 0.6657672170761176], 'avgF1': 0.7002223443577286, 'precision': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgPrecision': 0.704905523255814, 'recall': [0.6976744186046512, 0.7131782945736435, 0.7364341085271318, 0.7131782945736435, 0.6640625], 'avgRecall': 0.704905523255814, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.677036383162856, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7623788759689922, 'f1': [0.6745834332294414, 0.7681993100876813, 0.7818383167220376, 0.712020909247, 0.7003205128205128], 'avgF1': 0.7273924964213346, 'precision': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7623788759689922, 'recall': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7623788759689922, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7623788759689922, 'f1': [0.6745834332294414, 0.7681993100876813, 0.7818383167220376, 0.712020909247, 0.7003205128205128], 'avgF1': 0.7273924964213346, 'precision': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7623788759689922, 'recall': [0.7054263565891473, 0.7906976744186046, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7623788759689922, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.751441 0.733974 0.751441 0.751441
1 0.765504 0.742725 0.765504 0.765504
2 0.759266 0.707524 0.759266 0.759266
3 0.748437 0.677917 0.748437 0.748437
4 0.765480 0.743560 0.765480 0.765480
5 0.704906 0.700222 0.704906 0.704906
6 0.753113 0.677036 0.753113 0.753113
7 0.762379 0.727392 0.762379 0.762379
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgAccuracy': 0.7576550387596899, 'f1': [0.7198911429985156, 0.7933146969606852, 0.762015503875969, 0.7511767965557768, 0.6662999633296663], 'avgF1': 0.7385396207441226, 'precision': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgPrecision': 0.7576550387596899, 'recall': [0.7364341085271318, 0.8062015503875969, 0.7829457364341085, 0.7751937984496124, 0.6875], 'avgRecall': 0.7576550387596899, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6808189226793878, 0.7479232440415672, 0.7853697315626679, 0.7710053875124555, 0.7285067873303167], 'avgF1': 0.7427248146252791, 'precision': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7131782945736435, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgAccuracy': 0.759265988372093, 'f1': [0.664364575992483, 0.7697812954980905, 0.7501835985312117, 0.6986158120124709, 0.6546732837055418], 'avgF1': 0.7075237131479596, 'precision': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgPrecision': 0.759265988372093, 'recall': [0.7054263565891473, 0.8062015503875969, 0.7984496124031008, 0.7596899224806202, 0.7265625], 'avgRecall': 0.759265988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6809466545833873, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgAccuracy': 0.7654796511627907, 'f1': [0.7088378086789738, 0.7558764019683761, 0.77677987271754, 0.7599524823681759, 0.7163549688302163], 'avgF1': 0.7435603069126564, 'precision': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgPrecision': 0.7654796511627907, 'recall': [0.7364341085271318, 0.7751937984496124, 0.7906976744186046, 0.7906976744186046, 0.734375], 'avgRecall': 0.7654796511627907, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgAccuracy': 0.7079699612403101, 'f1': [0.7170891037366083, 0.7115949412610886, 0.6899224806201549, 0.7715825541436906, 0.640625], 'avgF1': 0.7061628159523085, 'precision': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgPrecision': 0.7079699612403101, 'recall': [0.7209302325581395, 0.7054263565891473, 0.689922480620155, 0.7829457364341085, 0.640625], 'avgRecall': 0.7079699612403101, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7685804263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.712020909247, 0.6865351629502573], 'avgF1': 0.7296590342546915, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7685804263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7685804263565892, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgAccuracy': 0.7685804263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.712020909247, 0.6865351629502573], 'avgF1': 0.7296590342546915, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgPrecision': 0.7685804263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.734375], 'avgRecall': 0.7685804263565892, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.757655 0.738540 0.757655 0.757655
1 0.765504 0.742725 0.765504 0.765504
2 0.759266 0.707524 0.759266 0.759266
3 0.753113 0.680947 0.753113 0.753113
4 0.765480 0.743560 0.765480 0.765480
5 0.707970 0.706163 0.707970 0.707970
6 0.754675 0.678040 0.754675 0.754675
7 0.768580 0.729659 0.768580 0.768580
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgAccuracy': 0.7576429263565891, 'f1': [0.748728722350895, 0.77677987271754, 0.762015503875969, 0.7550893344663139, 0.6606512890094979], 'avgF1': 0.7406529444840432, 'precision': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgPrecision': 0.7576429263565891, 'recall': [0.7596899224806202, 0.7906976744186046, 0.7829457364341085, 0.7751937984496124, 0.6796875], 'avgRecall': 0.7576429263565891, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgAccuracy': 0.7639413759689923, 'f1': [0.6870799332486183, 0.751726220852123, 0.7853697315626679, 0.7599524823681759, 0.7268656716417911], 'avgF1': 0.7421988079346752, 'precision': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgPrecision': 0.7639413759689923, 'recall': [0.7209302325581395, 0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7421875], 'avgRecall': 0.7639413759689923, 'params': [{'algorithm': 'kd_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7654917635658914, 'f1': [0.664364575992483, 0.7697812954980905, 0.7694002447980417, 0.6986158120124709, 0.6836642087351106], 'avgF1': 0.7171652274072393, 'precision': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7654917635658914, 'recall': [0.7054263565891473, 0.8062015503875969, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7654917635658914, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7531128875968992, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7223269781409317, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6809466545833873, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7531128875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7531128875968992, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgAccuracy': 0.7716448643410853, 'f1': [0.7431053760679646, 0.8331842576028622, 0.762015503875969, 0.7340165756285891, 0.6982720620647096], 'avgF1': 0.7541187550480188, 'precision': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgPrecision': 0.7716448643410853, 'recall': [0.7596899224806202, 0.8449612403100775, 0.7829457364341085, 0.7596899224806202, 0.7109375], 'avgRecall': 0.7716448643410853, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgAccuracy': 0.720421511627907, 'f1': [0.764240919780507, 0.733055058636454, 0.7142133544749825, 0.7224406745808836, 0.6598746081504703], 'avgF1': 0.7187649231246594, 'precision': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgPrecision': 0.720421511627907, 'recall': [0.7674418604651163, 0.7286821705426356, 0.7054263565891473, 0.7286821705426356, 0.671875], 'avgRecall': 0.720421511627907, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7701429263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7321070542918672, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7701429263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7701429263565892, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7701429263565892, 'f1': [0.6808189226793878, 0.7870818596747744, 0.7818383167220376, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7321070542918672, 'precision': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7701429263565892, 'recall': [0.7131782945736435, 0.813953488372093, 0.813953488372093, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7701429263565892, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.757643 0.740653 0.757643 0.757643
1 0.763941 0.742199 0.763941 0.763941
2 0.765492 0.717165 0.765492 0.765492
3 0.753113 0.680947 0.753113 0.753113
4 0.771645 0.754119 0.771645 0.771645
5 0.720422 0.718765 0.720422 0.720422
6 0.754675 0.678040 0.754675 0.754675
7 0.770143 0.732107 0.770143 0.770143
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'kd_tree', 'leaf_size': 30, 'met...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgAccuracy': 0.7529917635658915, 'f1': [0.7392681503709261, 0.7704639005158309, 0.762015503875969, 0.7446672012830794, 0.6606512890094979], 'avgF1': 0.7354132090110607, 'precision': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgPrecision': 0.7529917635658915, 'recall': [0.751937984496124, 0.7829457364341085, 0.7829457364341085, 0.7674418604651163, 0.6796875], 'avgRecall': 0.7529917635658915, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
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* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7655038759689923, 'f1': [0.6870799332486183, 0.7455346863590013, 0.7853697315626679, 0.7710053875124555, 0.733039970663733], 'avgF1': 0.7444059418692952, 'precision': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgPrecision': 0.7655038759689923, 'recall': [0.7209302325581395, 0.751937984496124, 0.8062015503875969, 0.7984496124031008, 0.75], 'avgRecall': 0.7655038759689923, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.664364575992483, 0.7818383167220376, 0.7694002447980417, 0.6986158120124709, 0.6836642087351106], 'avgF1': 0.7195766316520288, 'precision': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7054263565891473, 0.813953488372093, 0.813953488372093, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7546632751937984, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7276790369917914, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6820170663535592, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7546632751937984, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7546632751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgAccuracy': 0.774781976744186, 'f1': [0.7363964147673029, 0.7895486223865311, 0.7727125121774536, 0.7486206876588453, 0.7163549688302163], 'avgF1': 0.7527266411640698, 'precision': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgPrecision': 0.774781976744186, 'recall': [0.7596899224806202, 0.8062015503875969, 0.7906976744186046, 0.7829457364341085, 0.734375], 'avgRecall': 0.774781976744186, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgAccuracy': 0.7063832364341085, 'f1': [0.7013718317219756, 0.733055058636454, 0.7426608802784123, 0.7259513742071881, 0.622719734660033], 'avgF1': 0.7051517759008126, 'precision': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgPrecision': 0.7063832364341085, 'recall': [0.7054263565891473, 0.7286821705426356, 0.7441860465116279, 0.7364341085271318, 0.6171875], 'avgRecall': 0.7063832364341085, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.6808189226793878, 0.7681993100876813, 0.7881987918582434, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7296026394016897, 'precision': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.7670421511627907, 'f1': [0.6808189226793878, 0.7681993100876813, 0.7881987918582434, 0.7188538205980066, 0.6919423517851294], 'avgF1': 0.7296026394016897, 'precision': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.7670421511627907, 'recall': [0.7131782945736435, 0.7906976744186046, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.7670421511627907, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.752992 0.735413 0.752992 0.752992
1 0.765504 0.744406 0.765504 0.765504
2 0.767042 0.719577 0.767042 0.767042
3 0.754663 0.682017 0.754663 0.754663
4 0.774782 0.752727 0.774782 0.774782
5 0.706383 0.705152 0.706383 0.706383
6 0.754675 0.678040 0.754675 0.754675
7 0.767042 0.729603 0.767042 0.767042
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgAccuracy': 0.753015988372093, 'f1': [0.748728722350895, 0.7902163449359072, 0.7437102242312496, 0.7276450147019514, 0.6772048846675713], 'avgF1': 0.7375010381775149, 'precision': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgPrecision': 0.753015988372093, 'recall': [0.7596899224806202, 0.7984496124031008, 0.7596899224806202, 0.751937984496124, 0.6953125], 'avgRecall': 0.753015988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
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* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgAccuracy': 0.7701429263565891, 'f1': [0.7108921276253989, 0.751726220852123, 0.780725697856389, 0.7710053875124555, 0.7224184403754995], 'avgF1': 0.7473535748443731, 'precision': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgPrecision': 0.7701429263565891, 'recall': [0.7441860465116279, 0.7596899224806202, 0.8062015503875969, 0.7984496124031008, 0.7421875], 'avgRecall': 0.7701429263565891, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
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* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgAccuracy': 0.7701429263565891, 'f1': [0.6765196471531675, 0.7982676420278779, 0.7694002447980417, 0.6928223031968, 0.6993680884676144], 'avgF1': 0.7272755851287003, 'precision': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgPrecision': 0.7701429263565891, 'recall': [0.7209302325581395, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgRecall': 0.7701429263565891, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
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* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7546632751937984, 'f1': [0.6150153396175428, 0.7223269781409317, 0.7276790369917914, 0.6606878200386334, 0.6843761569788968], 'avgF1': 0.6820170663535592, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7546632751937984, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7906976744186046, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7546632751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
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* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgAccuracy': 0.7701187015503876, 'f1': [0.7534136170908624, 0.8331842576028622, 0.7579419364645084, 0.7276450147019514, 0.7003825920612148], 'avgF1': 0.7545134835842798, 'precision': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgPrecision': 0.7701187015503876, 'recall': [0.7596899224806202, 0.8449612403100775, 0.7674418604651163, 0.751937984496124, 0.7265625], 'avgRecall': 0.7701187015503876, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
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* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgAccuracy': 0.7219234496124031, 'f1': [0.7035077089671531, 0.7483090552857994, 0.7357085576812923, 0.7586565027709453, 0.6366810774858664], 'avgF1': 0.7165725804382113, 'precision': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgPrecision': 0.7219234496124031, 'recall': [0.7054263565891473, 0.7441860465116279, 0.7441860465116279, 0.7751937984496124, 0.640625], 'avgRecall': 0.7219234496124031, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
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* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
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* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.776344476744186, 'f1': [0.7044643814014727, 0.7998211091234347, 0.7822514111141063, 0.712020909247, 0.6993680884676144], 'avgF1': 0.7395851798707257, 'precision': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.776344476744186, 'recall': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.776344476744186, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgAccuracy': 0.776344476744186, 'f1': [0.7044643814014727, 0.7998211091234347, 0.7822514111141063, 0.712020909247, 0.6993680884676144], 'avgF1': 0.7395851798707257, 'precision': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgPrecision': 0.776344476744186, 'recall': [0.7364341085271318, 0.813953488372093, 0.8217054263565892, 0.7674418604651163, 0.7421875], 'avgRecall': 0.776344476744186, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.753016 0.737501 0.753016 0.753016
1 0.770143 0.747354 0.770143 0.770143
2 0.770143 0.727276 0.770143 0.770143
3 0.754663 0.682017 0.754663 0.754663
4 0.770119 0.754513 0.770119 0.770119
5 0.721923 0.716573 0.721923 0.721923
6 0.754675 0.678040 0.754675 0.754675
7 0.776344 0.739585 0.776344 0.776344
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgAccuracy': 0.753015988372093, 'f1': [0.7257877189626429, 0.7902163449359072, 0.7641862605550145, 0.738198943739853, 0.6719490658983177], 'avgF1': 0.738067666818347, 'precision': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgPrecision': 0.753015988372093, 'recall': [0.7364341085271318, 0.7984496124031008, 0.7751937984496124, 0.7596899224806202, 0.6953125], 'avgRecall': 0.753015988372093, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
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* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgAccuracy': 0.7701550387596899, 'f1': [0.7108921276253989, 0.751726220852123, 0.7790143964562569, 0.7665763528260706, 0.733039970663733], 'avgF1': 0.7482498136847165, 'precision': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgPrecision': 0.7701550387596899, 'recall': [0.7441860465116279, 0.7596899224806202, 0.7984496124031008, 0.7984496124031008, 0.75], 'avgRecall': 0.7701550387596899, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
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* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgAccuracy': 0.7685925387596899, 'f1': [0.6704274228850202, 0.7982676420278779, 0.7694002447980417, 0.6928223031968, 0.6993680884676144], 'avgF1': 0.7260571402750708, 'precision': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgPrecision': 0.7685925387596899, 'recall': [0.7131782945736435, 0.8217054263565892, 0.813953488372093, 0.751937984496124, 0.7421875], 'avgRecall': 0.7685925387596899, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
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* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
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* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgAccuracy': 0.7670300387596899, 'f1': [0.7465315046710396, 0.8331842576028622, 0.7677438840229539, 0.7044181622869307, 0.7062135922330097], 'avgF1': 0.7516182801633592, 'precision': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgPrecision': 0.7670300387596899, 'recall': [0.751937984496124, 0.8449612403100775, 0.7751937984496124, 0.7286821705426356, 0.734375], 'avgRecall': 0.7670300387596899, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgAccuracy': 0.7157703488372092, 'f1': [0.7215960192961348, 0.7788170485844904, 0.7302174632448992, 0.6685799109351804, 0.6682740272697041], 'avgF1': 0.7134968938660818, 'precision': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgPrecision': 0.7157703488372092, 'recall': [0.7286821705426356, 0.7751937984496124, 0.7286821705426356, 0.6744186046511628, 0.671875], 'avgRecall': 0.7157703488372092, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7732437015503876, 'f1': [0.7044643814014727, 0.7790143964562569, 0.7946447621079583, 0.6986158120124709, 0.6993680884676144], 'avgF1': 0.7352214880891547, 'precision': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7732437015503876, 'recall': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7732437015503876, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgAccuracy': 0.7732437015503876, 'f1': [0.7044643814014727, 0.7790143964562569, 0.7946447621079583, 0.6986158120124709, 0.6993680884676144], 'avgF1': 0.7352214880891547, 'precision': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgPrecision': 0.7732437015503876, 'recall': [0.7364341085271318, 0.7984496124031008, 0.8294573643410853, 0.7596899224806202, 0.7421875], 'avgRecall': 0.7732437015503876, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.753016 0.738068 0.753016 0.753016
1 0.770155 0.748250 0.770155 0.770155
2 0.768593 0.726057 0.768593 0.768593
3 0.756226 0.681065 0.756226 0.756226
4 0.767030 0.751618 0.767030 0.767030
5 0.715770 0.713497 0.715770 0.715770
6 0.754675 0.678040 0.754675 0.754675
7 0.773244 0.735221 0.773244 0.773244
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgAccuracy': 0.7297722868217055, 'f1': [0.664364575992483, 0.751937984496124, 0.7145288064176323, 0.6888272919587466, 0.687857142857143], 'avgF1': 0.7015031603444257, 'precision': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgPrecision': 0.7297722868217055, 'recall': [0.7054263565891473, 0.751937984496124, 0.7596899224806202, 0.7286821705426356, 0.703125], 'avgRecall': 0.7297722868217055, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgAccuracy': 0.7452640503875969, 'f1': [0.658327059920926, 0.733055058636454, 0.7579419364645084, 0.825234019247926, 0.6661406025824965], 'avgF1': 0.7281397353704622, 'precision': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgPrecision': 0.7452640503875969, 'recall': [0.6976744186046512, 0.7286821705426356, 0.7674418604651163, 0.8372093023255814, 0.6953125], 'avgRecall': 0.7452640503875969, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgAccuracy': 0.740625, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7276790369917914, 0.6700536672629696, 0.6776018099547512], 'avgF1': 0.697617257722345, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgPrecision': 0.740625, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7209302325581395, 0.703125], 'avgRecall': 0.740625, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgAccuracy': 0.6955668604651163, 'f1': [0.6853763660125872, 0.7593375616631429, 0.7036732313396307, 0.6311800172265288, 0.640625], 'avgF1': 0.6840384352483779, 'precision': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgPrecision': 0.6955668604651163, 'recall': [0.7131782945736435, 0.751937984496124, 0.7131782945736435, 0.6589147286821705, 0.640625], 'avgRecall': 0.6955668604651163, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7624152131782945, 'f1': [0.6758487491557502, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7098706206432376, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7624152131782945, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7624152131782945, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.729772 0.701503 0.729772 0.729772
1 0.745264 0.728140 0.745264 0.745264
2 0.763966 0.708802 0.763966 0.763966
3 0.756226 0.681065 0.756226 0.756226
4 0.740625 0.697617 0.740625 0.740625
5 0.695567 0.684038 0.695567 0.695567
6 0.754675 0.678040 0.754675 0.754675
7 0.762415 0.709871 0.762415 0.762415
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgAccuracy': 0.7297601744186046, 'f1': [0.658327059920926, 0.7456336082023335, 0.7254474314047425, 0.6947536921571692, 0.6719490658983177], 'avgF1': 0.6992221715166977, 'precision': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgPrecision': 0.7297601744186046, 'recall': [0.6976744186046512, 0.7441860465116279, 0.7751937984496124, 0.7364341085271318, 0.6953125], 'avgRecall': 0.7297601744186046, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgAccuracy': 0.7484011627906977, 'f1': [0.6452601712519633, 0.7329463027777849, 0.739643050297458, 0.7044614807057755, 0.6889320388349514], 'avgF1': 0.7022486087735866, 'precision': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgPrecision': 0.7484011627906977, 'recall': [0.7054263565891473, 0.7751937984496124, 0.7751937984496124, 0.7674418604651163, 0.71875], 'avgRecall': 0.7484011627906977, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.7639656007751938, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7421607654165794, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7088017227577472, 'precision': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgPrecision': 0.7639656007751938, 'recall': [0.7209302325581395, 0.7906976744186046, 0.7984496124031008, 0.751937984496124, 0.7578125], 'avgRecall': 0.7639656007751938, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7478509601775845, 0.6700536672629696, 0.7083333333333335], 'avgF1': 0.70779794703522, 'precision': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgAccuracy': 0.7018047480620155, 'f1': [0.6283914728682171, 0.7528617717451948, 0.7270645699922553, 0.6825359128470256, 0.6657672170761176], 'avgF1': 0.6913241889057621, 'precision': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgPrecision': 0.7018047480620155, 'recall': [0.6589147286821705, 0.7441860465116279, 0.7286821705426356, 0.7131782945736435, 0.6640625], 'avgRecall': 0.7018047480620155, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgAccuracy': 0.7639898255813954, 'f1': [0.6580489278163697, 0.7443820913078638, 0.7276790369917914, 0.6847589127528272, 0.7220079410096427], 'avgF1': 0.7073753819756989, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgPrecision': 0.7639898255813954, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgRecall': 0.7639898255813954, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgAccuracy': 0.7639898255813954, 'f1': [0.6580489278163697, 0.7443820913078638, 0.7276790369917914, 0.6847589127528272, 0.7220079410096427], 'avgF1': 0.7073753819756989, 'precision': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgPrecision': 0.7639898255813954, 'recall': [0.7131782945736435, 0.7906976744186046, 0.7906976744186046, 0.751937984496124, 0.7734375], 'avgRecall': 0.7639898255813954, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.729760 0.699222 0.729760 0.729760
1 0.748401 0.702249 0.748401 0.748401
2 0.763966 0.708802 0.763966 0.763966
3 0.756226 0.681065 0.756226 0.756226
4 0.756226 0.707798 0.756226 0.756226
5 0.701805 0.691324 0.701805 0.701805
6 0.754675 0.678040 0.754675 0.754675
7 0.763990 0.707375 0.763990 0.763990
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgAccuracy': 0.7266351744186047, 'f1': [0.6758487491557502, 0.7456336082023335, 0.7199701301472157, 0.6888272919587466, 0.6656528255311646], 'avgF1': 0.6991865209990421, 'precision': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgPrecision': 0.7266351744186047, 'recall': [0.7131782945736435, 0.7441860465116279, 0.7674418604651163, 0.7286821705426356, 0.6796875], 'avgRecall': 0.7266351744186047, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgAccuracy': 0.7561773255813954, 'f1': [0.7405131044665928, 0.7513637991379379, 0.6975037754791518, 0.6903912024517757, 0.7246603970741902], 'avgF1': 0.7208864557219297, 'precision': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgPrecision': 0.7561773255813954, 'recall': [0.7364341085271318, 0.7906976744186046, 0.7596899224806202, 0.7596899224806202, 0.734375], 'avgRecall': 0.7561773255813954, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgAccuracy': 0.765515988372093, 'f1': [0.6705042597282984, 0.7443820913078638, 0.7560514318380255, 0.6928223031968, 0.6941391941391942], 'avgF1': 0.7115798560420364, 'precision': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgPrecision': 0.765515988372093, 'recall': [0.7209302325581395, 0.7906976744186046, 0.8062015503875969, 0.751937984496124, 0.7578125], 'avgRecall': 0.765515988372093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6683696830943487, 0.7443820913078638, 0.7478509601775845, 0.6700536672629696, 0.7083333333333335], 'avgF1': 0.70779794703522, 'precision': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.8062015503875969, 0.7209302325581395, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgAccuracy': 0.6972141472868217, 'f1': [0.6559931379265853, 0.7142133544749825, 0.7053680713411435, 0.6310552500654623, 0.6962585034013606], 'avgF1': 0.6805776634419068, 'precision': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgPrecision': 0.6972141472868217, 'recall': [0.6821705426356589, 0.7054263565891473, 0.7286821705426356, 0.6666666666666666, 0.703125], 'avgRecall': 0.6972141472868217, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgAccuracy': 0.767078488372093, 'f1': [0.6826455239104355, 0.7386387881374012, 0.7560514318380255, 0.6847589127528272, 0.7083333333333335], 'avgF1': 0.7140855979944046, 'precision': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgPrecision': 0.767078488372093, 'recall': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgRecall': 0.767078488372093, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgAccuracy': 0.767078488372093, 'f1': [0.6826455239104355, 0.7386387881374012, 0.7560514318380255, 0.6847589127528272, 0.7083333333333335], 'avgF1': 0.7140855979944046, 'precision': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgPrecision': 0.767078488372093, 'recall': [0.7286821705426356, 0.7829457364341085, 0.8062015503875969, 0.751937984496124, 0.765625], 'avgRecall': 0.767078488372093, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.726635 0.699187 0.726635 0.726635
1 0.756177 0.720886 0.756177 0.756177
2 0.765516 0.711580 0.765516 0.765516
3 0.756226 0.681065 0.756226 0.756226
4 0.756226 0.707798 0.756226 0.756226
5 0.697214 0.680578 0.697214 0.697214
6 0.754675 0.678040 0.754675 0.754675
7 0.767078 0.714086 0.767078 0.767078
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgAccuracy': 0.7484617248062015, 'f1': [0.6405773857257417, 0.7633167512109851, 0.7309669522643819, 0.6517233154442457, 0.7028360748723765], 'avgF1': 0.6978840959035462, 'precision': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgPrecision': 0.7484617248062015, 'recall': [0.689922480620155, 0.8062015503875969, 0.7829457364341085, 0.7054263565891473, 0.7578125], 'avgRecall': 0.7484617248062015, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7531371124031008, 'f1': [0.6002214839424141, 0.707507113805998, 0.7176321353065539, 0.6555514540010664, 0.6944408532643827], 'avgF1': 0.675070608064083, 'precision': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7531371124031008, 'recall': [0.689922480620155, 0.7751937984496124, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7531371124031008, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7577640503875969, 'f1': [0.664364575992483, 0.7309669522643819, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.6966483784107219, 'precision': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7577640503875969, 'recall': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7577640503875969, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgAccuracy': 0.7112645348837209, 'f1': [0.6392123153864188, 0.7376730291609497, 0.6930159769989446, 0.6144154725550075, 0.7234133790737565], 'avgF1': 0.6815460346350154, 'precision': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgPrecision': 0.7112645348837209, 'recall': [0.6666666666666666, 0.751937984496124, 0.7286821705426356, 0.6434108527131783, 0.765625], 'avgRecall': 0.7112645348837209, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.664364575992483, 0.7309669522643819, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7010782164854198, 'precision': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.7054263565891473, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.748462 0.697884 0.748462 0.748462
1 0.753137 0.675071 0.753137 0.753137
2 0.757764 0.696648 0.757764 0.757764
3 0.756226 0.681065 0.756226 0.756226
4 0.763953 0.714847 0.763953 0.763953
5 0.711265 0.681546 0.711265 0.711265
6 0.754675 0.678040 0.754675 0.754675
7 0.759327 0.701078 0.759327 0.759327
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgAccuracy': 0.7422359496124031, 'f1': [0.6405773857257417, 0.7513637991379379, 0.7223269781409317, 0.6438815060908084, 0.6744062389223681], 'avgF1': 0.6865111816035576, 'precision': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgPrecision': 0.7422359496124031, 'recall': [0.689922480620155, 0.7906976744186046, 0.7829457364341085, 0.7054263565891473, 0.7421875], 'avgRecall': 0.7422359496124031, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7546875, 'f1': [0.6002214839424141, 0.7223269781409317, 0.7176321353065539, 0.6555514540010664, 0.6944408532643827], 'avgF1': 0.6780345809310697, 'precision': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7546875, 'recall': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7546875, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.697762097234859, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgAccuracy': 0.7096535852713178, 'f1': [0.6498236014111888, 0.7280177187153931, 0.7222041815502211, 0.6199662086546249, 0.6644923425978446], 'avgF1': 0.6769008105858545, 'precision': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgPrecision': 0.7096535852713178, 'recall': [0.6744186046511628, 0.751937984496124, 0.7441860465116279, 0.6511627906976745, 0.7265625], 'avgRecall': 0.7096535852713178, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.658327059920926, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7009844320952455, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6853763660125872, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.714847219077563, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.742236 0.686511 0.742236 0.742236
1 0.754687 0.678035 0.754687 0.754687
2 0.759314 0.697762 0.759314 0.759314
3 0.756226 0.681065 0.756226 0.756226
4 0.763953 0.714847 0.763953 0.763953
5 0.709654 0.676901 0.709654 0.709654
6 0.754675 0.678040 0.754675 0.754675
7 0.759327 0.700984 0.759327 0.759327
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgAccuracy': 0.7345082364341086, 'f1': [0.6338936219203315, 0.7513637991379379, 0.7013014721570301, 0.6281603080508689, 0.7028360748723765], 'avgF1': 0.6835110552277089, 'precision': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgPrecision': 0.7345082364341086, 'recall': [0.689922480620155, 0.7906976744186046, 0.751937984496124, 0.6821705426356589, 0.7578125], 'avgRecall': 0.7345082364341086, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgAccuracy': 0.7546875, 'f1': [0.6002214839424141, 0.7309669522643819, 0.7176321353065539, 0.6736236971466001, 0.6944408532643827], 'avgF1': 0.6833770243848666, 'precision': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgPrecision': 0.7546875, 'recall': [0.689922480620155, 0.7829457364341085, 0.7906976744186046, 0.7364341085271318, 0.7734375], 'avgRecall': 0.7546875, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 15, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.6941391941391942], 'avgF1': 0.697762097234859, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.7139357304109232, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgAccuracy': 0.7266957364341086, 'f1': [0.6727739604667519, 0.7397313848560582, 0.7161091462330323, 0.6532646967540319, 0.6826923076923077], 'avgF1': 0.6929142992004363, 'precision': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgPrecision': 0.7266957364341086, 'recall': [0.6976744186046512, 0.7674418604651163, 0.751937984496124, 0.6976744186046512, 0.71875], 'avgRecall': 0.7266957364341086, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.658327059920926, 0.7443820913078638, 0.7276790369917914, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7004456053468663, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7906976744186046, 0.7364341085271318, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgAccuracy': 0.763953488372093, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7633167512109851, 0.6870748139792838, 0.6686868686868686], 'avgF1': 0.7139357304109232, 'precision': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgPrecision': 0.763953488372093, 'recall': [0.7131782945736435, 0.8062015503875969, 0.8062015503875969, 0.7441860465116279, 0.75], 'avgRecall': 0.763953488372093, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.734508 0.683511 0.734508 0.734508
1 0.754687 0.683377 0.754687 0.754687
2 0.759314 0.697762 0.759314 0.759314
3 0.756226 0.681065 0.756226 0.756226
4 0.763953 0.713936 0.763953 0.763953
5 0.726696 0.692914 0.726696 0.726696
6 0.754675 0.678040 0.754675 0.754675
7 0.756226 0.700446 0.756226 0.756226
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7438105620155039, 'f1': [0.658327059920926, 0.7575987020010818, 0.6961113100574797, 0.6597275296914996, 0.7175882043180621], 'avgF1': 0.6978705611978099, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7438105620155039, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7441860465116279, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7438105620155039, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgAccuracy': 0.75625, 'f1': [0.6408053706861018, 0.7454780361757106, 0.7125512995896034, 0.6928223031968, 0.7194591984548527], 'avgF1': 0.7022232416206137, 'precision': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgPrecision': 0.75625, 'recall': [0.6821705426356589, 0.7829457364341085, 0.7829457364341085, 0.751937984496124, 0.78125], 'avgRecall': 0.75625, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7365355463850676, 0.7330833496189173, 0.6606878200386334, 0.7162883845126836], 'avgF1': 0.7021919353095569, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7501835985312117, 0.6756955814483354, 0.7175882043180621], 'avgF1': 0.7188135204950176, 'precision': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgAccuracy': 0.7221293604651163, 'f1': [0.6683696830943487, 0.7222041815502211, 0.7161091462330323, 0.6198182198610876, 0.7599728629579376], 'avgF1': 0.6972948187393255, 'precision': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgPrecision': 0.7221293604651163, 'recall': [0.6976744186046512, 0.7441860465116279, 0.751937984496124, 0.6434108527131783, 0.7734375], 'avgRecall': 0.7221293604651163, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7577761627906977, 'f1': [0.664364575992483, 0.7329463027777849, 0.7560514318380255, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7050404298244087, 'precision': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7577761627906977, 'recall': [0.7054263565891473, 0.7751937984496124, 0.8062015503875969, 0.7364341085271318, 0.765625], 'avgRecall': 0.7577761627906977, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6808189226793878, 0.7697812954980905, 0.7501835985312117, 0.6756955814483354, 0.7175882043180621], 'avgF1': 0.7188135204950176, 'precision': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7131782945736435, 0.8062015503875969, 0.7984496124031008, 0.7286821705426356, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.743811 0.697871 0.743811 0.743811
1 0.756250 0.702223 0.756250 0.756250
2 0.760877 0.702192 0.760877 0.760877
3 0.756226 0.681065 0.756226 0.756226
4 0.760865 0.718814 0.760865 0.760865
5 0.722129 0.697295 0.722129 0.722129
6 0.754675 0.678040 0.754675 0.754675
7 0.757776 0.705040 0.757776 0.757776
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgAccuracy': 0.7484617248062015, 'f1': [0.6585485164394547, 0.7443820913078638, 0.7199701301472157, 0.662624584717608, 0.7175882043180621], 'avgF1': 0.7006227053860409, 'precision': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgPrecision': 0.7484617248062015, 'recall': [0.7054263565891473, 0.7906976744186046, 0.7674418604651163, 0.7209302325581395, 0.7578125], 'avgRecall': 0.7484617248062015, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgAccuracy': 0.7578003875968992, 'f1': [0.6408053706861018, 0.7386387881374012, 0.7276790369917914, 0.6928223031968, 0.7194591984548527], 'avgF1': 0.7038809394933895, 'precision': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgPrecision': 0.7578003875968992, 'recall': [0.6821705426356589, 0.7829457364341085, 0.7906976744186046, 0.751937984496124, 0.78125], 'avgRecall': 0.7578003875968992, 'params': [{'algorithm': 'ball_tree', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7022897059083459, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgAccuracy': 0.7515503875968992, 'f1': [0.6727739604667519, 0.7513637991379379, 0.7223269781409317, 0.6813676633444076, 0.7118012422360248], 'avgF1': 0.7079267286652108, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgPrecision': 0.7515503875968992, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7364341085271318, 0.75], 'avgRecall': 0.7515503875968992, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgAccuracy': 0.7252059108527131, 'f1': [0.664364575992483, 0.7390402917592985, 0.7110188261351053, 0.6513617643151322, 0.734624581539933], 'avgF1': 0.7000820079483904, 'precision': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgPrecision': 0.7252059108527131, 'recall': [0.7054263565891473, 0.7596899224806202, 0.7364341085271318, 0.6666666666666666, 0.7578125], 'avgRecall': 0.7252059108527131, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7593265503875969, 'f1': [0.658327059920926, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7010822026940345, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7593265503875969, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7593265503875969, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.664364575992483, 0.7421607654165794, 0.7330833496189173, 0.6555514540010664, 0.7162883845126836], 'avgF1': 0.7022897059083459, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7364341085271318, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.748462 0.700623 0.748462 0.748462
1 0.757800 0.703881 0.757800 0.757800
2 0.760877 0.702290 0.760877 0.760877
3 0.756226 0.681065 0.756226 0.756226
4 0.751550 0.707927 0.751550 0.751550
5 0.725206 0.700082 0.725206 0.725206
6 0.754675 0.678040 0.754675 0.754675
7 0.759327 0.701082 0.759327 0.759327
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'ball_tree', 'leaf_size': 30, 'm...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgAccuracy': 0.7407218992248062, 'f1': [0.6635658914728682, 0.7755543537047053, 0.7037317468902109, 0.6333929636255217, 0.7355769230769231], 'avgF1': 0.7023643757540459, 'precision': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgPrecision': 0.7407218992248062, 'recall': [0.6976744186046512, 0.8062015503875969, 0.7441860465116279, 0.689922480620155, 0.765625], 'avgRecall': 0.7407218992248062, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.7063172311088063, 0.7694002447980417, 0.7024931908652838, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7165983418380591, 'precision': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.813953488372093, 0.7674418604651163, 0.7364341085271318, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7593144379844962, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7039740064855501, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7593144379844962, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7593144379844962, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7562257751937984, 'f1': [0.6150153396175428, 0.7276790369917914, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6810654871263021, 'precision': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7562257751937984, 'recall': [0.6976744186046512, 0.7906976744186046, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7562257751937984, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6664986680106559, 0.7633167512109851, 0.7170196609321097, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7103232245143829, 'precision': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.689922480620155, 0.8062015503875969, 0.7751937984496124, 0.7364341085271318, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgAccuracy': 0.7267684108527132, 'f1': [0.6683696830943487, 0.7558764019683761, 0.6823472027127483, 0.6587902280554744, 0.745475113122172], 'avgF1': 0.7021717257906239, 'precision': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgPrecision': 0.7267684108527132, 'recall': [0.6976744186046512, 0.7751937984496124, 0.7131782945736435, 0.6821705426356589, 0.765625], 'avgRecall': 0.7267684108527132, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6983351535007255, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7608769379844961, 'f1': [0.658327059920926, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6983351535007255, 'precision': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7608769379844961, 'recall': [0.6976744186046512, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.765625], 'avgRecall': 0.7608769379844961, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.740722 0.702364 0.740722 0.740722
1 0.756226 0.716598 0.756226 0.756226
2 0.759314 0.703974 0.759314 0.759314
3 0.756226 0.681065 0.756226 0.756226
4 0.754675 0.710323 0.754675 0.754675
5 0.726768 0.702172 0.726768 0.726768
6 0.754675 0.678040 0.754675 0.754675
7 0.760877 0.698335 0.760877 0.760877
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgAccuracy': 0.7453730620155039, 'f1': [0.6635658914728682, 0.7818383167220376, 0.7091177556293835, 0.6596027869484165, 0.7355769230769231], 'avgF1': 0.7099403347699258, 'precision': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgPrecision': 0.7453730620155039, 'recall': [0.6976744186046512, 0.813953488372093, 0.751937984496124, 0.6976744186046512, 0.765625], 'avgRecall': 0.7453730620155039, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.7070291844805862, 0.7694002447980417, 0.6975037754791518, 0.6813676633444076, 0.7234133790737565], 'avgF1': 0.7157428494351887, 'precision': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.813953488372093, 0.7596899224806202, 0.7364341085271318, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'uniform'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7562136627906977, 'f1': [0.658327059920926, 0.7125512995896034, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.6964475466972284, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7562136627906977, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7562136627906977, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgAccuracy': 0.6769258720930232, 'f1': [0.676594962309248, 0.6841180738534388, 0.7035224968465439, 0.7653217970740854, 0.6417397809970754], 'avgF1': 0.6942594222160783, 'precision': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgPrecision': 0.6769258720930232, 'recall': [0.6666666666666666, 0.6589147286821705, 0.6821705426356589, 0.7596899224806202, 0.6171875], 'avgRecall': 0.6769258720930232, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgAccuracy': 0.7546632751937985, 'f1': [0.6664986680106559, 0.7759761041177725, 0.7170196609321097, 0.6813676633444076, 0.7175882043180621], 'avgF1': 0.7116900601446016, 'precision': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgPrecision': 0.7546632751937985, 'recall': [0.689922480620155, 0.813953488372093, 0.7751937984496124, 0.7364341085271318, 0.7578125], 'avgRecall': 0.7546632751937985, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 50, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgAccuracy': 0.7220809108527132, 'f1': [0.6392123153864188, 0.762015503875969, 0.7166880456627216, 0.6528775050905584, 0.717503586800574], 'avgF1': 0.6976593913632484, 'precision': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgPrecision': 0.7220809108527132, 'recall': [0.6666666666666666, 0.7829457364341085, 0.7441860465116279, 0.6744186046511628, 0.7421875], 'avgRecall': 0.7220809108527132, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgAccuracy': 0.7546753875968992, 'f1': [0.6150153396175428, 0.7125512995896034, 0.7125512995896034, 0.6606878200386334, 0.6893939393939393], 'avgF1': 0.6780399396458645, 'precision': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgPrecision': 0.7546753875968992, 'recall': [0.6976744186046512, 0.7829457364341085, 0.7829457364341085, 0.7441860465116279, 0.765625], 'avgRecall': 0.7546753875968992, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6696954850957637, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7062476915205177, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgAccuracy': 0.7608648255813953, 'f1': [0.6696954850957637, 0.7501835985312117, 0.7330833496189173, 0.6606878200386334, 0.7175882043180621], 'avgF1': 0.7062476915205177, 'precision': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgPrecision': 0.7608648255813953, 'recall': [0.7054263565891473, 0.7984496124031008, 0.7984496124031008, 0.7441860465116279, 0.7578125], 'avgRecall': 0.7608648255813953, 'params': [{'activation': 'identity', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.745373 0.709940 0.745373 0.745373
1 0.754675 0.715743 0.754675 0.754675
2 0.756214 0.696448 0.756214 0.756214
3 0.676926 0.694259 0.676926 0.676926
4 0.754663 0.711690 0.754663 0.754663
5 0.722081 0.697659 0.722081 0.722081
6 0.754675 0.678040 0.754675 0.754675
7 0.760865 0.706248 0.760865 0.760865
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'identity', 'alpha': 0.0001, 'b...
now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))
Current date and time : 2021-06-05 11:25:12
# MSMOTE Dataset
X3 = pd.concat([X_msm, X_test_ord]) #.to_numpy()
y3 = pd.concat([y_msm, y_test_ord]).to_numpy()
#data = (X, y, n_folds)
print('********************************************')
print('Starting MSMOTE data set....')
print('********************************************')
for i in range(l ,6 , -1):
col = []
col = df[:i]
nX3 = X3.loc[:, col]
nX3 = nX3.to_numpy()
data3 = (nX3, y3, n_folds)
hyper_search(modelDictionary, modelParamsDictionary, data3, col)
********************************************
Starting MSMOTE data set....
********************************************
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgAccuracy': 0.9883794793088142, 'f1': [0.9743678853272765, 0.995916780089442, 0.9961302741477175, 1.0, 0.9793228295369784], 'avgF1': 0.9891475538202829, 'precision': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgPrecision': 0.9883794793088142, 'recall': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgRecall': 0.9883794793088142, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgAccuracy': 0.9858228411099283, 'f1': [0.9676739206610505, 0.9970868129733929, 0.9969026764273867, 0.9982541222114452, 0.9758846916161877], 'avgF1': 0.9871604447778926, 'precision': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgPrecision': 0.9858228411099283, 'recall': [0.9686289697908598, 0.9941905499612703, 0.9969016266460109, 0.9965143299767621, 0.9728787291747385], 'avgRecall': 0.9858228411099283, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgAccuracy': 0.7098884147426631, 'f1': [0.777423060191904, 0.8231540565177757, 0.7867707062024818, 0.798510935318753, 0.7804853075974088], 'avgF1': 0.7932688131656647, 'precision': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgPrecision': 0.7098884147426631, 'recall': [0.7405112316034083, 0.6994577846630519, 0.7854376452362509, 0.6646010844306739, 0.6594343277799303], 'avgRecall': 0.7098884147426631, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 1000, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'lbfgs', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgAccuracy': 0.5707191713501903, 'f1': [0.25640924396388326, 0.23271731690622857, 0.3812585496570828, 1.0, 0.9790648204787236], 'avgF1': 0.5698899862011836, 'precision': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgPrecision': 0.5707191713501903, 'recall': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgRecall': 0.5707191713501903, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgAccuracy': 0.8232986932151206, 'f1': [0.8633451762715798, 0.9045396690708528, 0.8738148077694966, 0.8781229632848142, 0.8663113674226026], 'avgF1': 0.8772267967638692, 'precision': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgPrecision': 0.8232986932151206, 'recall': [0.84856700232378, 0.82571649883811, 0.8733539891556933, 0.7827265685515105, 0.7861294072065091], 'avgRecall': 0.8232986932151206, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgAccuracy': 0.9859004505006046, 'f1': [0.9691002688487015, 0.9965021375825883, 0.9938094503299437, 0.9990308199263424, 0.9771374854420583], 'avgF1': 0.9871160324259268, 'precision': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgPrecision': 0.9859004505006046, 'recall': [0.9697908597986057, 0.9930286599535244, 0.9938032532920217, 0.9980635166537568, 0.9748159628051143], 'avgRecall': 0.9859004505006046, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgAccuracy': 0.7166262363557079, 'f1': [0.7800883034515573, 0.8570163789287295, 0.8019796875306643, 0.781500707881076, 0.769455076002716], 'avgF1': 0.7980080307589487, 'precision': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgPrecision': 0.7166262363557079, 'recall': [0.7447714949651433, 0.7498063516653757, 0.8024786986831913, 0.6413632842757552, 0.644711352189074], 'avgRecall': 0.7166262363557079, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgAccuracy': 0.9157143710323099, 'f1': [0.9305101722946922, 0.9717244125846276, 0.9382817272666095, 0.9433190096173522, 0.9184272413709469], 'avgF1': 0.9404525126268457, 'precision': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgPrecision': 0.9157143710323099, 'recall': [0.9298993028659953, 0.9450038729666925, 0.9384198295894656, 0.8927188226181255, 0.8725300271212708], 'avgRecall': 0.9157143710323099, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?, Severity of Crypt Arch', 'accuracy': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgAccuracy': 0.9883794793088142, 'f1': [0.9743678853272765, 0.995916780089442, 0.9961302741477175, 1.0, 0.9793228295369784], 'avgF1': 0.9891475538202829, 'precision': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgPrecision': 0.9883794793088142, 'recall': [0.9748257164988381, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9790778767919411], 'avgRecall': 0.9883794793088142, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.988379 0.989148 0.988379 0.988379
1 0.985823 0.987160 0.985823 0.985823
2 0.709888 0.793269 0.709888 0.709888
3 0.570719 0.569890 0.570719 0.570719
4 0.823299 0.877227 0.823299 0.823299
5 0.985900 0.987116 0.985900 0.985900
6 0.716626 0.798008 0.716626 0.716626
7 0.915714 0.940453 0.915714 0.915714
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9883020499863299, 'f1': [0.9731674659131014, 0.9961119751166407, 0.9961302741477175, 1.0, 0.9798216331902337], 'avgF1': 0.9890462696735387, 'precision': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9883020499863299, 'recall': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9883020499863299, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgAccuracy': 0.9860551891001123, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9758248309524068], 'avgF1': 0.9874394568321025, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgPrecision': 0.9860551891001123, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgRecall': 0.9860551891001123, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgAccuracy': 0.7080290606052512, 'f1': [0.7764548243144944, 0.8231540565177757, 0.7829940556967838, 0.798510935318753, 0.7773747131425005], 'avgF1': 0.7916977169980615, 'precision': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgPrecision': 0.7080290606052512, 'recall': [0.7393493415956622, 0.6994577846630519, 0.7815646785437645, 0.6646010844306739, 0.6551724137931034], 'avgRecall': 0.7080290606052512, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'lbfgs', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgAccuracy': 0.5707191713501903, 'f1': [0.25640924396388326, 0.23271731690622857, 0.3812585496570828, 1.0, 0.9790648204787236], 'avgF1': 0.5698899862011836, 'precision': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgPrecision': 0.5707191713501903, 'recall': [0.26103795507358635, 0.13168086754453912, 0.4763749031758327, 1.0, 0.9845021309569935], 'avgRecall': 0.5707191713501903, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgAccuracy': 0.8246153518337395, 'f1': [0.8637356720609862, 0.9003407155025552, 0.8795433200600168, 0.8839420791009294, 0.8650952794461256], 'avgF1': 0.8785314132341226, 'precision': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgPrecision': 0.8246153518337395, 'recall': [0.8489542989930287, 0.8187451587916343, 0.879163439194423, 0.7920216886134779, 0.7841921735761332], 'avgRecall': 0.8246153518337395, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgAccuracy': 0.9864425157807262, 'f1': [0.9727905244243396, 0.9965021375825883, 0.9941930054144381, 0.9994187173028483, 0.9760735647130044], 'avgF1': 0.9877955898874438, 'precision': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgPrecision': 0.9864425157807262, 'recall': [0.9732765298218435, 0.9930286599535244, 0.9941905499612703, 0.9988381099922541, 0.9728787291747385], 'avgRecall': 0.9864425157807262, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgAccuracy': 0.7132954249774389, 'f1': [0.7806913607465088, 0.8488631297369593, 0.798284941105791, 0.7812131224923295, 0.7688794517439788], 'avgF1': 0.7955864011651135, 'precision': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgPrecision': 0.7132954249774389, 'recall': [0.7455460883036406, 0.737412858249419, 0.7986057319907048, 0.6409759876065065, 0.6439364587369236], 'avgRecall': 0.7132954249774389, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgAccuracy': 0.9147847990033826, 'f1': [0.936057893349985, 0.9731556969576457, 0.9356754163792643, 0.9376671466776383, 0.9179313583397674], 'avgF1': 0.9400975023408601, 'precision': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgPrecision': 0.9147847990033826, 'recall': [0.9360960495739736, 0.947714949651433, 0.935708752904725, 0.8826491092176607, 0.8717551336691205], 'avgRecall': 0.9147847990033826, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent, Mild & superficial increase in lamina propria cellularity?', 'accuracy': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9883020499863299, 'f1': [0.9731674659131014, 0.9961119751166407, 0.9961302741477175, 1.0, 0.9798216331902337], 'avgF1': 0.9890462696735387, 'precision': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9883020499863299, 'recall': [0.9736638264910922, 0.9922540666150271, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9883020499863299, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.988302 0.989046 0.988302 0.988302
1 0.986055 0.987439 0.986055 0.986055
2 0.708029 0.791698 0.708029 0.708029
3 0.570719 0.569890 0.570719 0.570719
4 0.824615 0.878531 0.824615 0.824615
5 0.986443 0.987796 0.986443 0.986443
6 0.713295 0.795586 0.713295 0.713295
7 0.914785 0.940098 0.914785 0.914785
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9882245906524801, 'f1': [0.9732022021645715, 0.995916780089442, 0.9961302741477175, 1.0, 0.9795870048608761], 'avgF1': 0.9889672522525215, 'precision': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9882245906524801, 'recall': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9882245906524801, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgAccuracy': 0.9860551891001123, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9758248309524068], 'avgF1': 0.9874394568321025, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgPrecision': 0.9860551891001123, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9724912824486633], 'avgRecall': 0.9860551891001123, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgAccuracy': 0.709191040647093, 'f1': [0.7776698727945794, 0.8239580961056706, 0.7841127237588575, 0.7990697674418605, 0.7782246345606274], 'avgF1': 0.7926070189323191, 'precision': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgPrecision': 0.709191040647093, 'recall': [0.7408985282726569, 0.7006196746707978, 0.7827265685515105, 0.6653756777691712, 0.6563347539713289], 'avgRecall': 0.709191040647093, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgAccuracy': 0.8242277850622031, 'f1': [0.8609623792963672, 0.9059322033898305, 0.8794362077842383, 0.8812824956672444, 0.8628947564914238], 'avgF1': 0.8781016085258209, 'precision': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgPrecision': 0.8242277850622031, 'recall': [0.8454686289697909, 0.8280402788536019, 0.879163439194423, 0.7877614252517429, 0.7807051530414568], 'avgRecall': 0.8242277850622031, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgAccuracy': 0.9858231412235814, 'f1': [0.9728605242690611, 0.995916780089442, 0.9938084386363477, 0.9966971051097725, 0.9779936838309122], 'avgF1': 0.9874553063871071, 'precision': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgPrecision': 0.9858231412235814, 'recall': [0.9732765298218435, 0.9918667699457785, 0.9938032532920217, 0.993415956622773, 0.9767531964354901], 'avgRecall': 0.9858231412235814, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgAccuracy': 0.7137601809805373, 'f1': [0.7803898504701119, 0.85040071237756, 0.798284941105791, 0.781500707881076, 0.7688794517439788], 'avgF1': 0.7958911327157036, 'precision': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgPrecision': 0.7137601809805373, 'recall': [0.7451587916343919, 0.7397366382649109, 0.7986057319907048, 0.6413632842757552, 0.6439364587369236], 'avgRecall': 0.7137601809805373, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgAccuracy': 0.9190461427742687, 'f1': [0.9230897102695093, 0.9731556969576457, 0.9409482185752528, 0.9469820554649266, 0.9260389794402553], 'avgF1': 0.9420429321415179, 'precision': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgPrecision': 0.9190461427742687, 'recall': [0.9213787761425252, 0.947714949651433, 0.941130906274206, 0.8993028659953525, 0.8857032158078264], 'avgRecall': 0.9190461427742687, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles, Crypt abscesses extent', 'accuracy': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgAccuracy': 0.9882245906524801, 'f1': [0.9732022021645715, 0.995916780089442, 0.9961302741477175, 1.0, 0.9795870048608761], 'avgF1': 0.9889672522525215, 'precision': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgPrecision': 0.9882245906524801, 'recall': [0.9736638264910922, 0.9918667699457785, 0.9961270333075135, 1.0, 0.9794653235180163], 'avgRecall': 0.9882245906524801, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.988225 0.988967 0.988225 0.988225
1 0.986055 0.987439 0.986055 0.986055
2 0.709191 0.792607 0.709191 0.709191
3 0.562276 0.555955 0.562276 0.562276
4 0.824228 0.878102 0.824228 0.824228
5 0.985823 0.987455 0.985823 0.985823
6 0.713760 0.795891 0.713760 0.713760
7 0.919046 0.942043 0.919046 0.919046
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727905244243396, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890544460397829, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgAccuracy': 0.9862876571357573, 'f1': [0.9689345541874661, 0.9970868129733929, 0.9969026764273867, 0.9984484096198604, 0.9765737004271536], 'avgF1': 0.987589230727052, 'precision': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgPrecision': 0.9862876571357573, 'recall': [0.9697908597986057, 0.9941905499612703, 0.9969016266460109, 0.9969016266460109, 0.9736536226268888], 'avgRecall': 0.9862876571357573, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgAccuracy': 0.7120576962495697, 'f1': [0.7806325273130154, 0.8255628837843983, 0.7875879074837805, 0.7965509205313449, 0.7843592268776751], 'avgF1': 0.7949386931980429, 'precision': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgPrecision': 0.7120576962495697, 'recall': [0.7443841982958946, 0.7029434546862897, 0.7862122385747483, 0.6618900077459334, 0.6648585819449826], 'avgRecall': 0.7120576962495697, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgAccuracy': 0.8160947050648081, 'f1': [0.8463246441406662, 0.8963453729429365, 0.8828871178796518, 0.8737186477644493, 0.8641182709362619], 'avgF1': 0.8726788107327932, 'precision': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgPrecision': 0.8160947050648081, 'recall': [0.8272656855151046, 0.8121611154144074, 0.8826491092176607, 0.7757552285050349, 0.7826423866718326], 'avgRecall': 0.8160947050648081, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgAccuracy': 0.9859777597776278, 'f1': [0.9704626603534707, 0.9963070942662778, 0.9953555638756445, 0.9990308199263424, 0.9758846916161877], 'avgF1': 0.9874081660075846, 'precision': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgPrecision': 0.9859777597776278, 'recall': [0.9709527498063517, 0.9926413632842758, 0.9953524399690162, 0.9980635166537568, 0.9728787291747385], 'avgRecall': 0.9859777597776278, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgAccuracy': 0.7144578852011256, 'f1': [0.7797223424168295, 0.8491196790728773, 0.7954013243870571, 0.7829366014612302, 0.774395356274719], 'avgF1': 0.7963150607225427, 'precision': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgPrecision': 0.7144578852011256, 'recall': [0.7443841982958946, 0.7378001549186677, 0.7955073586367157, 0.6432997676219985, 0.6512979465323518], 'avgRecall': 0.7144578852011256, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgAccuracy': 0.9173420674409399, 'f1': [0.9210585051803777, 0.9729514717581542, 0.9421193137385487, 0.9431027425296765, 0.9261480658251595], 'avgF1': 0.9410760198063833, 'precision': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgPrecision': 0.9173420674409399, 'recall': [0.9186676994577847, 0.9473276529821844, 0.942292796281952, 0.8923315259488769, 0.8860906625339016], 'avgRecall': 0.9173420674409399, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs, Crypt profiles', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727905244243396, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890544460397829, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.988380 0.989054 0.988380 0.988380
1 0.986288 0.987589 0.986288 0.986288
2 0.712058 0.794939 0.712058 0.712058
3 0.562276 0.555955 0.562276 0.562276
4 0.816095 0.872679 0.816095 0.816095
5 0.985978 0.987408 0.985978 0.985978
6 0.714458 0.796315 0.714458 0.714458
7 0.917342 0.941076 0.917342 0.917342
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727551528306728, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890473717210495, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
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* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgAccuracy': 0.9865200351373065, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9986426216792708, 0.9765737004271536], 'avgF1': 0.987744408663813, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgPrecision': 0.9865200351373065, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9972889233152595, 0.9736536226268888], 'avgRecall': 0.9865200351373065, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgAccuracy': 0.7118244479184267, 'f1': [0.786274850083763, 0.8260968401909524, 0.7921825020771343, 0.7948658109684947, 0.776172039127646], 'avgF1': 0.795118408489598, 'precision': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgPrecision': 0.7118244479184267, 'recall': [0.7513555383423702, 0.703718048024787, 0.790859798605732, 0.6595662277304415, 0.6536226268888028], 'avgRecall': 0.7118244479184267, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgAccuracy': 0.8033907140634159, 'f1': [0.8461028615839487, 0.8812824956672444, 0.868733105193608, 0.8638063806380638, 0.8587159127126046], 'avgF1': 0.8637281511590938, 'precision': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgPrecision': 0.8033907140634159, 'recall': [0.8264910921766073, 0.7877614252517429, 0.8683191324554609, 0.7602633617350891, 0.774118558698179], 'avgRecall': 0.8033907140634159, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgAccuracy': 0.9865975544938869, 'f1': [0.9735792048758081, 0.9951352403191283, 0.9953563289772609, 0.9994187173028483, 0.9757930522140035], 'avgF1': 0.9878565087378098, 'precision': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgPrecision': 0.9865975544938869, 'recall': [0.9740511231603408, 0.9903175832687839, 0.9953524399690162, 0.9988381099922541, 0.9744285160790391], 'avgRecall': 0.9865975544938869, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgAccuracy': 0.7184077710228864, 'f1': [0.7870151680116803, 0.8575221238938054, 0.806195271360556, 0.7780407004259348, 0.7692399404136899], 'avgF1': 0.7996026408211333, 'precision': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgPrecision': 0.7184077710228864, 'recall': [0.7536793183578622, 0.750580945003873, 0.8067389620449265, 0.6367157242447715, 0.6443239054629989], 'avgRecall': 0.7184077710228864, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgAccuracy': 0.9102142181244037, 'f1': [0.9209775162588809, 0.9721337579617836, 0.93897590349354, 0.9372298826919118, 0.9143682896876353], 'avgF1': 0.9367370700187503, 'precision': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgPrecision': 0.9102142181244037, 'recall': [0.9186676994577847, 0.9457784663051898, 0.9391944229279628, 0.8818745158791634, 0.8655559860519179], 'avgRecall': 0.9102142181244037, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes, Crypt abscesses polymorphs', 'accuracy': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgAccuracy': 0.9883795393315449, 'f1': [0.9727551528306728, 0.9961119751166407, 0.9965169604138426, 1.0, 0.9798527702440915], 'avgF1': 0.9890473717210495, 'precision': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgPrecision': 0.9883795393315449, 'recall': [0.9732765298218435, 0.9922540666150271, 0.9965143299767621, 1.0, 0.9798527702440915], 'avgRecall': 0.9883795393315449, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.988380 0.989047 0.988380 0.988380
1 0.986520 0.987744 0.986520 0.986520
2 0.711824 0.795118 0.711824 0.711824
3 0.562276 0.555955 0.562276 0.562276
4 0.803391 0.863728 0.803391 0.803391
5 0.986598 0.987857 0.986598 0.986598
6 0.718408 0.799603 0.718408 0.718408
7 0.910214 0.936737 0.910214 0.910214
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgAccuracy': 0.9879147233057158, 'f1': [0.9723782737340749, 0.9957215091404122, 0.9965169604138426, 0.999806314158435, 0.9793228295369784], 'avgF1': 0.9887491773967486, 'precision': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgPrecision': 0.9879147233057158, 'recall': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgRecall': 0.9879147233057158, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgAccuracy': 0.9863651464809723, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9980597594101667, 0.9766334901142151], 'avgF1': 0.9876397941474044, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgPrecision': 0.9863651464809723, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.974041069352964], 'avgRecall': 0.9863651464809723, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgAccuracy': 0.7161628308640482, 'f1': [0.7877340247253514, 0.8314098212265219, 0.7914359526380598, 0.797951582867784, 0.7824565269482253], 'avgF1': 0.7981975816811885, 'precision': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgPrecision': 0.7161628308640482, 'recall': [0.7532920216886135, 0.7114639814097599, 0.7900852052672347, 0.6638264910921766, 0.6621464548624564], 'avgRecall': 0.7161628308640482, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgAccuracy': 0.8038547197823815, 'f1': [0.8372517832882455, 0.8764142732811141, 0.8679986680680337, 0.8832179930795847, 0.8525553749749708], 'avgF1': 0.8634876185383897, 'precision': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgPrecision': 0.8038547197823815, 'recall': [0.8164213787761425, 0.78001549186677, 0.8675445391169636, 0.790859798605732, 0.7644323905462999], 'avgRecall': 0.8038547197823815, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgAccuracy': 0.985668132521786, 'f1': [0.9688066242554079, 0.9955261622252479, 0.99574082141404, 0.9982541222114452, 0.9774420173402057], 'avgF1': 0.9871539494892694, 'precision': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgPrecision': 0.985668132521786, 'recall': [0.969403563129357, 0.9910921766072812, 0.9957397366382649, 0.9965143299767621, 0.9755908562572646], 'avgRecall': 0.985668132521786, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgAccuracy': 0.7135272627744127, 'f1': [0.7867820788492016, 0.8582799027194339, 0.7971253059938356, 0.7719381688466113, 0.7638266856189538], 'avgF1': 0.7955904284056072, 'precision': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgPrecision': 0.7135272627744127, 'recall': [0.7532920216886135, 0.7517428350116189, 0.7970565453137103, 0.62858249419055, 0.6369624176675707], 'avgRecall': 0.7135272627744127, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgAccuracy': 0.9041737706069288, 'f1': [0.920560326588896, 0.9731556969576457, 0.9402613094813305, 0.907783417935702, 0.924646238552518], 'avgF1': 0.9332813979032184, 'precision': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgPrecision': 0.9041737706069288, 'recall': [0.9182804027885361, 0.947714949651433, 0.9403563129357088, 0.831138652207591, 0.8833785354513755], 'avgRecall': 0.9041737706069288, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age, Intraepithelial lymphocytes', 'accuracy': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgAccuracy': 0.9879147233057158, 'f1': [0.9723782737340749, 0.9957215091404122, 0.9965169604138426, 0.999806314158435, 0.9793228295369784], 'avgF1': 0.9887491773967486, 'precision': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgPrecision': 0.9879147233057158, 'recall': [0.9728892331525949, 0.9914794732765299, 0.9965143299767621, 0.9996127033307514, 0.9790778767919411], 'avgRecall': 0.9879147233057158, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.987915 0.988749 0.987915 0.987915
1 0.986365 0.987640 0.986365 0.986365
2 0.716163 0.798198 0.716163 0.716163
3 0.562276 0.555955 0.562276 0.562276
4 0.803855 0.863488 0.803855 0.803855
5 0.985668 0.987154 0.985668 0.985668
6 0.713527 0.795590 0.713527 0.713527
7 0.904174 0.933281 0.904174 0.904174
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgAccuracy': 0.9879148133398118, 'f1': [0.9715890815550484, 0.9955261622252479, 0.9965169604138426, 0.999806314158435, 0.98012018747861], 'avgF1': 0.9887117411662368, 'precision': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgPrecision': 0.9879148133398118, 'recall': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgRecall': 0.9879148133398118, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgAccuracy': 0.9862876571357573, 'f1': [0.9689345541874661, 0.9972815533980581, 0.9972896136271163, 0.9980597594101667, 0.9763829613145928], 'avgF1': 0.98758968838748, 'precision': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgPrecision': 0.9862876571357573, 'recall': [0.9697908597986057, 0.994577846630519, 0.9972889233152595, 0.9961270333075135, 0.9736536226268888], 'avgRecall': 0.9862876571357573, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgAccuracy': 0.7209651294945396, 'f1': [0.7933676263388896, 0.8387677085675735, 0.7989463800654896, 0.7982313241796601, 0.7807027206038801], 'avgF1': 0.8020031519510986, 'precision': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgPrecision': 0.7209651294945396, 'recall': [0.7606506584043378, 0.7223082881487219, 0.7978311386522076, 0.6642137877614253, 0.6598217745060054], 'avgRecall': 0.7209651294945396, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgAccuracy': 0.8068759039048088, 'f1': [0.834074527907235, 0.8868290579866351, 0.8736302403662103, 0.8790970262643802, 0.8547786046065992], 'avgF1': 0.865681891426212, 'precision': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgPrecision': 0.8068759039048088, 'recall': [0.8121611154144074, 0.7966692486444616, 0.8733539891556933, 0.784275755228505, 0.7679194110809764], 'avgRecall': 0.8068759039048088, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgAccuracy': 0.9864426658375527, 'f1': [0.9723059961548532, 0.9963070942662778, 0.9953563289772609, 0.9982541222114452, 0.9762780159978284], 'avgF1': 0.9877003115215331, 'precision': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgPrecision': 0.9864426658375527, 'recall': [0.9728892331525949, 0.9926413632842758, 0.9953524399690162, 0.9965143299767621, 0.9748159628051143], 'avgRecall': 0.9864426658375527, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgAccuracy': 0.7156186647883553, 'f1': [0.7882181347268206, 0.8620537681798148, 0.7995753784801307, 0.7719381688466113, 0.7638266856189538], 'avgF1': 0.7971224271704662, 'precision': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgPrecision': 0.7156186647883553, 'recall': [0.7552285050348567, 0.7575522850503486, 0.7997676219984509, 0.62858249419055, 0.6369624176675707], 'avgRecall': 0.7156186647883553, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgAccuracy': 0.8979740827851508, 'f1': [0.9275046500660639, 0.9632603894800242, 0.9570873638940116, 0.9080143793613872, 0.9025412197478779], 'avgF1': 0.9316816005098729, 'precision': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgPrecision': 0.8979740827851508, 'recall': [0.9264136328427576, 0.929124709527498, 0.9573973663826492, 0.8315259488768396, 0.8454087562960093], 'avgRecall': 0.8979740827851508, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?, Age', 'accuracy': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgAccuracy': 0.9879148133398118, 'f1': [0.9715890815550484, 0.9955261622252479, 0.9965169604138426, 0.999806314158435, 0.98012018747861], 'avgF1': 0.9887117411662368, 'precision': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgPrecision': 0.9879148133398118, 'recall': [0.9721146398140976, 0.9910921766072812, 0.9965143299767621, 0.9996127033307514, 0.9802402169701666], 'avgRecall': 0.9879148133398118, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.987915 0.988712 0.987915 0.987915
1 0.986288 0.987590 0.986288 0.986288
2 0.720965 0.802003 0.720965 0.720965
3 0.562276 0.555955 0.562276 0.562276
4 0.806876 0.865682 0.806876 0.806876
5 0.986443 0.987700 0.986443 0.986443
6 0.715619 0.797122 0.715619 0.715619
7 0.897974 0.931682 0.897974 0.897974
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgAccuracy': 0.8853440998105983, 'f1': [0.9318672032153393, 0.984863377236092, 0.9239980821952671, 0.8927958833619212, 0.8701985112564117], 'avgF1': 0.9207446114530062, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgPrecision': 0.8853440998105983, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgRecall': 0.8853440998105983, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgAccuracy': 0.8827109026188218, 'f1': [0.9292289271642805, 0.9713147410358566, 0.9245789359229387, 0.897994024754588, 0.8735873898087486], 'avgF1': 0.9193408037372824, 'precision': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgPrecision': 0.8827109026188218, 'recall': [0.9306738962044926, 0.9442292796281953, 0.9260263361735089, 0.814872192099148, 0.797752808988764], 'avgRecall': 0.8827109026188218, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgAccuracy': 0.7088038940346709, 'f1': [0.8170071032689387, 0.7648887825878976, 0.8057433323606248, 0.8004645760743322, 0.7795732053514963], 'avgF1': 0.793535399928658, 'precision': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgPrecision': 0.7088038940346709, 'recall': [0.7931835786212239, 0.6192873741285825, 0.8059643687064292, 0.6673121611154144, 0.6582719876017048], 'avgRecall': 0.7088038940346709, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgAccuracy': 0.7524924889055485, 'f1': [0.8251407686907716, 0.8783666377063423, 0.8194261688719104, 0.8084910013844023, 0.7938195078211951], 'avgF1': 0.8250488168949244, 'precision': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgPrecision': 0.7524924889055485, 'recall': [0.8032532920216886, 0.7831138652207591, 0.8195197521301317, 0.6785437645236251, 0.6780317706315382], 'avgRecall': 0.7524924889055485, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgAccuracy': 0.8836398143977124, 'f1': [0.9290421309803026, 0.9840645288215619, 0.9235778993761502, 0.8916076411247048, 0.8687425347188019], 'avgF1': 0.9194069470043043, 'precision': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgPrecision': 0.8836398143977124, 'recall': [0.9306738962044926, 0.9686289697908598, 0.9244771494965144, 0.8044151820294345, 0.7900038744672607], 'avgRecall': 0.8836398143977124, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgAccuracy': 0.7395533588569991, 'f1': [0.8310493187351712, 0.8904168457241083, 0.815700526111898, 0.7754327721128764, 0.7613468292498494], 'avgF1': 0.8147892583867806, 'precision': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgPrecision': 0.7395533588569991, 'recall': [0.8109992254066615, 0.8024786986831913, 0.8171959721146398, 0.6332300542215337, 0.6338628438589694], 'avgRecall': 0.7395533588569991, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgAccuracy': 0.8828655511842335, 'f1': [0.9275816441579903, 0.9822625147812375, 0.918431958676894, 0.8930332261521973, 0.8714083132864341], 'avgF1': 0.9185435314109506, 'precision': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgPrecision': 0.8828655511842335, 'recall': [0.9287374128582494, 0.965143299767622, 0.919442292796282, 0.8067389620449265, 0.7942657884540876], 'avgRecall': 0.8828655511842335, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?, Increased lymphoid aggregates in lamina propria?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgAccuracy': 0.8853440998105983, 'f1': [0.9318672032153393, 0.984863377236092, 0.9239980821952671, 0.8927958833619212, 0.8701985112564117], 'avgF1': 0.9207446114530062, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgPrecision': 0.8853440998105983, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8063516653756778, 0.7923285548237118], 'avgRecall': 0.8853440998105983, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.885344 0.920745 0.885344 0.885344
1 0.882711 0.919341 0.882711 0.882711
2 0.708804 0.793535 0.708804 0.708804
3 0.562276 0.555955 0.562276 0.562276
4 0.752492 0.825049 0.752492 0.752492
5 0.883640 0.919407 0.883640 0.883640
6 0.739553 0.814789 0.739553 0.739553
7 0.882866 0.918544 0.882866 0.882866
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgAccuracy': 0.8855765978576087, 'f1': [0.9320414800091605, 0.984863377236092, 0.9239980821952671, 0.8925584387733219, 0.8711665843469139], 'avgF1': 0.9209255925121511, 'precision': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgPrecision': 0.8855765978576087, 'recall': [0.9329976762199845, 0.9701781564678543, 0.924864446165763, 0.8059643687064292, 0.7938783417280124], 'avgRecall': 0.8855765978576087, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgAccuracy': 0.8875901503899527, 'f1': [0.9281835117085948, 0.9925868123293016, 0.9175891771378678, 0.8982291444420738, 0.8680051095162222], 'avgF1': 0.9209187510268121, 'precision': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgPrecision': 0.8875901503899527, 'recall': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgRecall': 0.8875901503899527, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgAccuracy': 0.7002828571179905, 'f1': [0.8135087148490493, 0.751148730350665, 0.8027809827234254, 0.7928938756428238, 0.7745422804888014], 'avgF1': 0.786974916810953, 'precision': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgPrecision': 0.7002828571179905, 'recall': [0.7885360185902401, 0.6014717273431448, 0.80286599535244, 0.656855151045701, 0.651685393258427], 'avgRecall': 0.7002828571179905, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgAccuracy': 0.7651978904411101, 'f1': [0.8251407686907716, 0.8783666377063423, 0.822400087921541, 0.8319384754580411, 0.8125309123058684], 'avgF1': 0.8340753764165129, 'precision': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgPrecision': 0.7651978904411101, 'recall': [0.8032532920216886, 0.7831138652207591, 0.8226181254841208, 0.7122385747482571, 0.7047655947307245], 'avgRecall': 0.7651978904411101, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgAccuracy': 0.8834848357072823, 'f1': [0.9286244191421082, 0.9850628930817611, 0.9228132529623144, 0.8913696865607557, 0.8682488838367678], 'avgF1': 0.9192238271167414, 'precision': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgPrecision': 0.8834848357072823, 'recall': [0.9298993028659953, 0.9705654531371031, 0.923702556158017, 0.8040278853601859, 0.7892289810151104], 'avgRecall': 0.8834848357072823, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgAccuracy': 0.7243707892178768, 'f1': [0.8203832924383659, 0.8521893754167594, 0.8145075947224464, 0.7800614221592251, 0.7559959193065631], 'avgF1': 0.804627520808672, 'precision': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgPrecision': 0.7243707892178768, 'recall': [0.7974438419829589, 0.7424477149496514, 0.8156467854376452, 0.639426800929512, 0.6268888027896165], 'avgRecall': 0.7243707892178768, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgAccuracy': 0.8795348598514258, 'f1': [0.925692038022254, 0.9808565225971977, 0.9180707244508202, 0.8856279671989642, 0.8718899656420951], 'avgF1': 0.9164274435822662, 'precision': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgPrecision': 0.8795348598514258, 'recall': [0.9264136328427576, 0.9624322230828815, 0.9190549961270333, 0.7947327652982185, 0.7950406819062379], 'avgRecall': 0.8795348598514258, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex, Increased lamina propria cellularity?', 'accuracy': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgAccuracy': 0.8875901503899527, 'f1': [0.9281835117085948, 0.9925868123293016, 0.9175891771378678, 0.8982291444420738, 0.8680051095162222], 'avgF1': 0.9209187510268121, 'precision': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgPrecision': 0.8875901503899527, 'recall': [0.9295120061967467, 0.9852827265685515, 0.9190549961270333, 0.8152594887683966, 0.7888415342890353], 'avgRecall': 0.8875901503899527, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.885577 0.920926 0.885577 0.885577
1 0.887590 0.920919 0.887590 0.887590
2 0.700283 0.786975 0.700283 0.700283
3 0.562276 0.555955 0.562276 0.562276
4 0.765198 0.834075 0.765198 0.765198
5 0.883485 0.919224 0.883485 0.883485
6 0.724371 0.804628 0.724371 0.724371
7 0.879535 0.916427 0.879535 0.879535
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgAccuracy': 0.8903808172154795, 'f1': [0.9315174243667953, 0.984863377236092, 0.9239980821952671, 0.8937446443873178, 0.885076746436222], 'avgF1': 0.9238400549243388, 'precision': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgPrecision': 0.8903808172154795, 'recall': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgRecall': 0.8903808172154795, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgAccuracy': 0.8856535469982483, 'f1': [0.9282764822640005, 0.9923902439024389, 0.9224118228753246, 0.890893470790378, 0.8670290327476512], 'avgF1': 0.9202002105159587, 'precision': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgPrecision': 0.8856535469982483, 'recall': [0.9295120061967467, 0.9848954298993029, 0.9233152594887684, 0.8032532920216886, 0.7872917473847346], 'avgRecall': 0.8856535469982483, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgAccuracy': 0.6669730326874788, 'f1': [0.7078962045168463, 0.7550626808100289, 0.8201163419931231, 0.7731052506533619, 0.7521595579342258], 'avgF1': 0.7616680071815172, 'precision': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgPrecision': 0.6669730326874788, 'recall': [0.6537567776917118, 0.6065065840433772, 0.8226181254841208, 0.6301316808675446, 0.6218519953506393], 'avgRecall': 0.6669730326874788, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgAccuracy': 0.702068533353581, 'f1': [0.6997310918189729, 0.7637060090974384, 0.8306460431433276, 0.8319384754580411, 0.8125309123058684], 'avgF1': 0.7877105063647296, 'precision': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgPrecision': 0.702068533353581, 'recall': [0.6440743609604958, 0.6177381874515879, 0.8315259488768396, 0.7122385747482571, 0.7047655947307245], 'avgRecall': 0.702068533353581, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 20, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgAccuracy': 0.8887541411932699, 'f1': [0.9288080419231897, 0.9838646202282565, 0.9228132529623144, 0.8925584387733219, 0.8848593922885515], 'avgF1': 0.9225807492351268, 'precision': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgPrecision': 0.8887541411932699, 'recall': [0.9298993028659953, 0.9682416731216111, 0.923702556158017, 0.8059643687064292, 0.8159628051142968], 'avgRecall': 0.8887541411932699, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgAccuracy': 0.6982650129604081, 'f1': [0.8284850975609559, 0.7760132732875089, 0.8242609930903515, 0.765774378585086, 0.7361743533334244], 'avgF1': 0.7861416191714653, 'precision': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgPrecision': 0.6982650129604081, 'recall': [0.808288148721921, 0.6340046475600309, 0.8272656855151046, 0.6204492641363284, 0.6013173188686556], 'avgRecall': 0.6982650129604081, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgAccuracy': 0.8872816935773578, 'f1': [0.9260369304242264, 0.9798498617147372, 0.9176683932444094, 0.9033765130600976, 0.8791246839616708], 'avgF1': 0.9212112764810283, 'precision': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgPrecision': 0.8872816935773578, 'recall': [0.9268009295120062, 0.9604957397366383, 0.9186676994577847, 0.8237800154918667, 0.8066640836884929], 'avgRecall': 0.8872816935773578, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?, Sex', 'accuracy': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgAccuracy': 0.8903808172154795, 'f1': [0.9315174243667953, 0.984863377236092, 0.9239980821952671, 0.8937446443873178, 0.885076746436222], 'avgF1': 0.9238400549243388, 'precision': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgPrecision': 0.8903808172154795, 'recall': [0.9326103795507359, 0.9701781564678543, 0.924864446165763, 0.8079008520526724, 0.8163502518403719], 'avgRecall': 0.8903808172154795, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.890381 0.923840 0.890381 0.890381
1 0.885654 0.920200 0.885654 0.885654
2 0.666973 0.761668 0.666973 0.666973
3 0.562276 0.555955 0.562276 0.562276
4 0.702069 0.787711 0.702069 0.702069
5 0.888754 0.922581 0.888754 0.888754
6 0.698265 0.786142 0.698265 0.698265
7 0.887282 0.921211 0.887282 0.887282
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
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* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9134793606749531, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648212048724403], 'avgF1': 0.9112572633443916, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgAccuracy': 0.8699284619085248, 'f1': [0.9045965385958659, 0.9747865793130831, 0.9062460614636522, 0.8961094484822573, 0.8601426360762431], 'avgF1': 0.9083762527862203, 'precision': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgPrecision': 0.8699284619085248, 'recall': [0.9027885360185902, 0.9508133230054222, 0.9078233927188226, 0.8117738187451587, 0.77644323905463], 'avgRecall': 0.8699284619085248, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgAccuracy': 0.7160802996094621, 'f1': [0.8247083735709287, 0.8562569213732003, 0.8154433366621827, 0.7616306954436451, 0.732808466145676], 'avgF1': 0.7981695586391265, 'precision': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgPrecision': 0.7160802996094621, 'recall': [0.8036405886909372, 0.7486444616576298, 0.8164213787761425, 0.6150271107668474, 0.5966679581557536], 'avgRecall': 0.7160802996094621, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgAccuracy': 0.7614793622344782, 'f1': [0.8198155911067191, 0.8781229632848142, 0.8166686000561928, 0.8314098212265219, 0.8084146843926965], 'avgF1': 0.8308863320133889, 'precision': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgPrecision': 0.7614793622344782, 'recall': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgRecall': 0.7614793622344782, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgAccuracy': 0.8714004593539574, 'f1': [0.9125480515766394, 0.9743793445878849, 0.9067042559189009, 0.8930332261521973, 0.8623710770429008], 'avgF1': 0.9098071910557046, 'precision': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgPrecision': 0.8714004593539574, 'recall': [0.9120836560805577, 0.9500387296669248, 0.9082106893880713, 0.8067389620449265, 0.7799302595893065], 'avgRecall': 0.8714004593539574, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgAccuracy': 0.7242170710047895, 'f1': [0.8064685534997607, 0.8645558487247141, 0.8141613484696684, 0.7660692951015531, 0.7675787821565135], 'avgF1': 0.8037667655904419, 'precision': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgPrecision': 0.7242170710047895, 'recall': [0.7804027885360186, 0.761425251742835, 0.8160340821068939, 0.620836560805577, 0.642386671832623], 'avgRecall': 0.7242170710047895, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgAccuracy': 0.8574562186700103, 'f1': [0.9058081232777009, 0.9684378745505393, 0.8985338577449483, 0.8790970262643802, 0.8494006558466097], 'avgF1': 0.9002555075368357, 'precision': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgPrecision': 0.8574562186700103, 'recall': [0.9043377226955848, 0.9388071262587142, 0.9000774593338497, 0.784275755228505, 0.759783029833398], 'avgRecall': 0.8574562186700103, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
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*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells, Active inflammation?', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9134793606749531, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648212048724403], 'avgF1': 0.9112572633443916, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.873337 0.911257 0.873337 0.873337
1 0.869928 0.908376 0.869928 0.869928
2 0.716080 0.798170 0.716080 0.716080
3 0.562276 0.555955 0.562276 0.562276
4 0.761479 0.830886 0.761479 0.761479
5 0.871400 0.909807 0.871400 0.871400
6 0.724217 0.803767 0.724217 0.724217
7 0.857456 0.900256 0.857456 0.857456
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9133815972723025, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648271003331741], 'avgF1': 0.9112388897560083, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgAccuracy': 0.8624146664341786, 'f1': [0.9031920905673471, 0.9659591509811776, 0.9002910214348246, 0.889701139539884, 0.8581618283570202], 'avgF1': 0.9034610461760507, 'precision': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgPrecision': 0.8624146664341786, 'recall': [0.9016266460108443, 0.9341595662277304, 0.9016266460108443, 0.8013168086754454, 0.7733436652460287], 'avgRecall': 0.8624146664341786, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 17, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgAccuracy': 0.7180941522554591, 'f1': [0.8270991185513474, 0.8625550660792951, 0.8165922249067556, 0.759548402594283, 0.7318926918225436], 'avgF1': 0.799537500790845, 'precision': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgPrecision': 0.7180941522554591, 'recall': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6123160340821069, 0.5955056179775281], 'avgRecall': 0.7180941522554591, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgAccuracy': 0.7614793622344782, 'f1': [0.8198155911067191, 0.8781229632848142, 0.8166686000561928, 0.8314098212265219, 0.8084146843926965], 'avgF1': 0.8308863320133889, 'precision': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgPrecision': 0.7614793622344782, 'recall': [0.7970565453137103, 0.7827265685515105, 0.8175832687838884, 0.7114639814097599, 0.6985664471135219], 'avgRecall': 0.7614793622344782, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgAccuracy': 0.8709358834190508, 'f1': [0.9058226669293736, 0.9749900754267568, 0.907922863761689, 0.8932704672096015, 0.8638521812514545], 'avgF1': 0.909171650915775, 'precision': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgPrecision': 0.8709358834190508, 'recall': [0.9047250193648335, 0.9512006196746708, 0.9093725793958172, 0.8071262587141751, 0.7822549399457575], 'avgRecall': 0.8709358834190508, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgAccuracy': 0.7150733882921463, 'f1': [0.805336920369519, 0.8692796146266697, 0.8139814356233989, 0.7604416706673068, 0.733128262891943], 'avgF1': 0.7964335808357674, 'precision': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgPrecision': 0.7150733882921463, 'recall': [0.7796281951975214, 0.7687838884585593, 0.8160340821068939, 0.6134779240898528, 0.5974428516079039], 'avgRecall': 0.7150733882921463, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgAccuracy': 0.8568365139878472, 'f1': [0.9042683325944265, 0.9682317682317682, 0.8986047311033807, 0.8786102062975025, 0.8491306029432546], 'avgF1': 0.8997691282340665, 'precision': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgPrecision': 0.8568365139878472, 'recall': [0.9024012393493416, 0.9384198295894656, 0.9004647560030984, 0.7835011618900077, 0.7593955831073227], 'avgRecall': 0.8568365139878472, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs, Basal histiocytic cells', 'accuracy': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgAccuracy': 0.8733372428138536, 'f1': [0.9133815972723025, 0.9749900754267568, 0.9083038949258901, 0.8946917808219178, 0.8648271003331741], 'avgF1': 0.9112388897560083, 'precision': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgPrecision': 0.8733372428138536, 'recall': [0.9124709527498064, 0.9512006196746708, 0.9097598760650658, 0.8094500387296669, 0.7838047268500581], 'avgRecall': 0.8733372428138536, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.873337 0.911239 0.873337 0.873337
1 0.862415 0.903461 0.862415 0.862415
2 0.718094 0.799538 0.718094 0.718094
3 0.562276 0.555955 0.562276 0.562276
4 0.761479 0.830886 0.761479 0.761479
5 0.870936 0.909172 0.870936 0.870936
6 0.715073 0.796434 0.715073 0.715073
7 0.856837 0.899769 0.856837 0.856837
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgAccuracy': 0.871632777332776, 'f1': [0.9129489803012953, 0.9749900754267568, 0.905865172416312, 0.8939815806382522, 0.8618786720632232], 'avgF1': 0.909932896169168, 'precision': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgPrecision': 0.871632777332776, 'recall': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgRecall': 0.871632777332776, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgAccuracy': 0.8660550150341935, 'f1': [0.9136219438937164, 0.9674065186962608, 0.9058128139987781, 0.889701139539884, 0.8561744926373911], 'avgF1': 0.906543381753206, 'precision': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgPrecision': 0.8660550150341935, 'recall': [0.9144074360960496, 0.9368706429124709, 0.907436096049574, 0.8013168086754454, 0.7702440914374273], 'avgRecall': 0.8660550150341935, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 14, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgAccuracy': 0.7180166929216094, 'f1': [0.8270991185513474, 0.8625550660792951, 0.8165922249067556, 0.7592503604036521, 0.7318926918225436], 'avgF1': 0.7994778923527188, 'precision': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgPrecision': 0.7180166929216094, 'recall': [0.8067389620449265, 0.7583268783888458, 0.8175832687838884, 0.6119287374128582, 0.5955056179775281], 'avgRecall': 0.7180166929216094, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5622761639833005, 'f1': [0.23210809566060528, 0.20382608695652168, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5559552737554982, 'precision': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5622761639833005, 'recall': [0.24593338497288925, 0.11347792408985283, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5622761639833005, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgAccuracy': 0.762099126939372, 'f1': [0.8228027997729285, 0.8778791829639285, 0.8166686000561928, 0.8303510758776897, 0.8092211059284697], 'avgF1': 0.8313845529198418, 'precision': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgPrecision': 0.762099126939372, 'recall': [0.8009295120061968, 0.7823392718822618, 0.8175832687838884, 0.7099147947327653, 0.6997287872917474], 'avgRecall': 0.762099126939372, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgAccuracy': 0.8686889324987372, 'f1': [0.9091471938599553, 0.9749900754267568, 0.9050511083456165, 0.8904168457241083, 0.858657640209762], 'avgF1': 0.9076525727132397, 'precision': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgPrecision': 0.8686889324987372, 'recall': [0.9089852827265685, 0.9512006196746708, 0.9066615027110767, 0.8024786986831913, 0.774118558698179], 'avgRecall': 0.8686889324987372, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgAccuracy': 0.7131366348436153, 'f1': [0.805336920369519, 0.8680403331871986, 0.8127836382107109, 0.7580567580567581, 0.7303740855092412], 'avgF1': 0.7949183470666855, 'precision': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgPrecision': 0.7131366348436153, 'recall': [0.7796281951975214, 0.7668474051123161, 0.814872192099148, 0.6103795507358637, 0.5939558310732275], 'avgRecall': 0.7131366348436153, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgAccuracy': 0.8504843384189592, 'f1': [0.8966769958192552, 0.963884430176565, 0.8919130556138197, 0.8776352966746359, 0.844829384749791], 'avgF1': 0.8949878326068134, 'precision': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgPrecision': 0.8504843384189592, 'recall': [0.8934934159566228, 0.930286599535244, 0.8938807126258714, 0.7819519752130132, 0.7528089887640449], 'avgRecall': 0.8504843384189592, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs, Cryptitis polymorphs', 'accuracy': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgAccuracy': 0.871632777332776, 'f1': [0.9129489803012953, 0.9749900754267568, 0.905865172416312, 0.8939815806382522, 0.8618786720632232], 'avgF1': 0.909932896169168, 'precision': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgPrecision': 0.871632777332776, 'recall': [0.9120836560805577, 0.9512006196746708, 0.907436096049574, 0.808288148721921, 0.7791553661371562], 'avgRecall': 0.871632777332776, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.871633 0.909933 0.871633 0.871633
1 0.866055 0.906543 0.866055 0.866055
2 0.718017 0.799478 0.718017 0.718017
3 0.562276 0.555955 0.562276 0.562276
4 0.762099 0.831385 0.762099 0.762099
5 0.868689 0.907653 0.868689 0.868689
6 0.713137 0.794918 0.713137 0.713137
7 0.850484 0.894988 0.850484 0.850484
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgAccuracy': 0.8707807246604289, 'f1': [0.910617074792847, 0.9749900754267568, 0.904927397758066, 0.8937446443873178, 0.861862044195941], 'avgF1': 0.9092282473121858, 'precision': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgPrecision': 0.8707807246604289, 'recall': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgRecall': 0.8707807246604289, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgAccuracy': 0.8681465370935973, 'f1': [0.9065883363039315, 0.9790431000395413, 0.9029503227136623, 0.8889845094664374, 0.857168979814244], 'avgF1': 0.9069470496675633, 'precision': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgPrecision': 0.8681465370935973, 'recall': [0.9054996127033308, 0.9589465530596437, 0.9043377226955848, 0.8001549186676995, 0.771793878341728], 'avgRecall': 0.8681465370935973, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgAccuracy': 0.7125166600591644, 'f1': [0.8206411285065356, 0.8597924486641644, 0.8162220567606543, 0.7520541324311262, 0.7276013289453526], 'avgF1': 0.7952622190615666, 'precision': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgPrecision': 0.7125166600591644, 'recall': [0.7986057319907048, 0.7540666150271108, 0.8171959721146398, 0.6026336173508908, 0.5900813638124758], 'avgRecall': 0.7125166600591644, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgAccuracy': 0.7589226340014964, 'f1': [0.8215160665131502, 0.8749455337690631, 0.8102413246989624, 0.8337850045167119, 0.8030842271732835], 'avgF1': 0.8287144313342343, 'precision': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgPrecision': 0.7589226340014964, 'recall': [0.7993803253292022, 0.7776917118512781, 0.8113865220759101, 0.7149496514329977, 0.6912049593180938], 'avgRecall': 0.7589226340014964, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 100, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgAccuracy': 0.8683793052428955, 'f1': [0.9050454360167915, 0.9749900754267568, 0.9029503227136623, 0.8925584387733219, 0.8603801813279701], 'avgF1': 0.9071848908517005, 'precision': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgPrecision': 0.8683793052428955, 'recall': [0.9035631293570875, 0.9512006196746708, 0.9043377226955848, 0.8059643687064292, 0.7768306857807051], 'avgRecall': 0.8683793052428955, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgAccuracy': 0.7201110360493519, 'f1': [0.80631773797358, 0.8665496049165935, 0.8105596685886568, 0.757459095283927, 0.7609770506087514], 'avgF1': 0.8003726314743017, 'precision': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgPrecision': 0.7201110360493519, 'recall': [0.7807900852052673, 0.7645236250968241, 0.8121611154144074, 0.6096049573973664, 0.6334753971328942], 'avgRecall': 0.7201110360493519, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgAccuracy': 0.8483149668779567, 'f1': [0.9059391834928153, 0.9624271649588104, 0.8866709665438921, 0.8724890829694323, 0.84044762324625], 'avgF1': 0.89359480424224, 'precision': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgPrecision': 0.8483149668779567, 'recall': [0.9051123160340822, 0.9275755228505035, 0.888845855925639, 0.7738187451587917, 0.7462223944207671], 'avgRecall': 0.8483149668779567, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent, Lamina propria polymorphs', 'accuracy': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgAccuracy': 0.8707807246604289, 'f1': [0.910617074792847, 0.9749900754267568, 0.904927397758066, 0.8937446443873178, 0.861862044195941], 'avgF1': 0.9092282473121858, 'precision': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgPrecision': 0.8707807246604289, 'recall': [0.9093725793958172, 0.9512006196746708, 0.9062742060418281, 0.8079008520526724, 0.7791553661371562], 'avgRecall': 0.8707807246604289, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 500, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.870781 0.909228 0.870781 0.870781
1 0.868147 0.906947 0.868147 0.868147
2 0.712517 0.795262 0.712517 0.712517
3 0.562354 0.556080 0.562354 0.562354
4 0.758923 0.828714 0.758923 0.758923
5 0.868379 0.907185 0.868379 0.868379
6 0.720111 0.800373 0.720111 0.720111
7 0.848315 0.893595 0.848315 0.848315
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgAccuracy': 0.8681470172754422, 'f1': [0.9089591438613208, 0.9727471653073403, 0.9033304862958237, 0.8911316298045953, 0.8611215657346356], 'avgF1': 0.9074579982007431, 'precision': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgPrecision': 0.8681470172754422, 'recall': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgRecall': 0.8681470172754422, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgAccuracy': 0.8494009281314834, 'f1': [0.9060333350386341, 0.9618013671089667, 0.9020107293732391, 0.8549889135254989, 0.8534311499792596], 'avgF1': 0.8956530990051197, 'precision': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgPrecision': 0.8494009281314834, 'recall': [0.9047250193648335, 0.9264136328427576, 0.9031758326878389, 0.7467079783113865, 0.7659821774506005], 'avgRecall': 0.8494009281314834, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 16, 'p': 2, 'weights': 'distance'}]}
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Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgAccuracy': 0.7060876553950981, 'f1': [0.8133089364082086, 0.8450011183180496, 0.8122921048657172, 0.7532592950265572, 0.7288304256934545], 'avgF1': 0.7905383760623974, 'precision': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgPrecision': 0.7060876553950981, 'recall': [0.7893106119287374, 0.7316034082106894, 0.813710302091402, 0.6041828040278854, 0.5916311507167764], 'avgRecall': 0.7060876553950981, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'multinomial', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
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Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgAccuracy': 0.7540429360598859, 'f1': [0.8082803494249249, 0.8761697497279651, 0.8115102256268, 0.8239580961056706, 0.8053049218925732], 'avgF1': 0.8250446685555868, 'precision': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgPrecision': 0.7540429360598859, 'recall': [0.7831138652207591, 0.7796281951975214, 0.8125484120836561, 0.7006196746707978, 0.694304533126695], 'avgRecall': 0.7540429360598859, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgAccuracy': 0.8655130097768025, 'f1': [0.9072308539360908, 0.9725427775567052, 0.9025445552900987, 0.8877880680594443, 0.8578784379915173], 'avgF1': 0.9055969385667713, 'precision': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgPrecision': 0.8655130097768025, 'recall': [0.9058869093725794, 0.9465530596436871, 0.9039504260263361, 0.7982184353214562, 0.7729562185199536], 'avgRecall': 0.8655130097768025, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgAccuracy': 0.72034380419865, 'f1': [0.8047639669500705, 0.8670469504168494, 0.8087749101136529, 0.75626204238921, 0.7648348961392571], 'avgF1': 0.800336553201808, 'precision': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgPrecision': 0.72034380419865, 'recall': [0.7792408985282726, 0.7652982184353214, 0.8106119287374128, 0.6080557707203718, 0.6385122045718714], 'avgRecall': 0.72034380419865, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
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Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgAccuracy': 0.843512728270196, 'f1': [0.8954807035948079, 0.9516849370686156, 0.8880317078810531, 0.8756803831918136, 0.8424693327575392], 'avgF1': 0.8906694128987659, 'precision': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgPrecision': 0.843512728270196, 'recall': [0.8915569326103796, 0.9078233927188226, 0.8900077459333849, 0.778853601859024, 0.7493219682293685], 'avgRecall': 0.843512728270196, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'invscaling', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 7000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas, Cryptitis extent', 'accuracy': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgAccuracy': 0.8681470172754422, 'f1': [0.9089591438613208, 0.9727471653073403, 0.9033304862958237, 0.8911316298045953, 0.8611215657346356], 'avgF1': 0.9074579982007431, 'precision': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgPrecision': 0.8681470172754422, 'recall': [0.907436096049574, 0.9469403563129357, 0.9047250193648335, 0.8036405886909372, 0.7779930259589306], 'avgRecall': 0.8681470172754422, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': False, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.868147 0.907458 0.868147 0.868147
1 0.849401 0.895653 0.849401 0.849401
2 0.706088 0.790538 0.706088 0.706088
3 0.562354 0.556080 0.562354 0.562354
4 0.754043 0.825045 0.754043 0.754043
5 0.865513 0.905597 0.865513 0.865513
6 0.720344 0.800337 0.720344 0.720344
7 0.843513 0.890669 0.843513 0.843513
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgAccuracy': 0.8528078183207981, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8900492682245151, 0.8737186477644493, 0.8422848050693988], 'avgF1': 0.8961204878211272, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgPrecision': 0.8528078183207981, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgRecall': 0.8528078183207981, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
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Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgAccuracy': 0.8441320428046101, 'f1': [0.9131760617034314, 0.9721337579617836, 0.8895032429297922, 0.8395505617977529, 0.8394983217203529], 'avgF1': 0.8907723892226226, 'precision': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgPrecision': 0.8441320428046101, 'recall': [0.9155693261037955, 0.9457784663051898, 0.8911696359411309, 0.7234701781564679, 0.7446726075164665], 'avgRecall': 0.8441320428046101, 'params': [{'algorithm': 'brute', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 13, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgAccuracy': 0.704227490950823, 'f1': [0.8003500340001569, 0.8747003704510786, 0.7993560957994182, 0.7456886082098615, 0.7167332306608132], 'avgF1': 0.7873656678242656, 'precision': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgPrecision': 0.704227490950823, 'recall': [0.7726568551510457, 0.7773044151820294, 0.7997676219984509, 0.5945003872966692, 0.5769081751259202], 'avgRecall': 0.704227490950823, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
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Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgAccuracy': 0.5623536233171502, 'f1': [0.23210809566060528, 0.20445062586926283, 0.3642745251823215, 1.0, 0.979567660978043], 'avgF1': 0.5560801815380465, 'precision': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgPrecision': 0.5623536233171502, 'recall': [0.24593338497288925, 0.11386522075910147, 0.4666924864446166, 1.0, 0.9852770244091438], 'avgRecall': 0.5623536233171502, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgAccuracy': 0.7535773697499243, 'f1': [0.8198695777300405, 0.8761697497279651, 0.8013882497041634, 0.8260968401909524, 0.7978933029226667], 'avgF1': 0.8242835440551577, 'precision': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgPrecision': 0.7535773697499243, 'recall': [0.7989930286599535, 0.7796281951975214, 0.801704105344694, 0.703718048024787, 0.6838434715226657], 'avgRecall': 0.7535773697499243, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
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Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgAccuracy': 0.8511810822758579, 'f1': [0.9001232520618444, 0.9723383084577115, 0.8884729136470888, 0.8715034965034966, 0.8414954182769057], 'avgF1': 0.8947866777894093, 'precision': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgPrecision': 0.8511810822758579, 'recall': [0.8993028659953525, 0.9461657629744384, 0.8903950426026336, 0.772269558481797, 0.7477721813250678], 'avgRecall': 0.8511810822758579, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'random'}]}
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Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgAccuracy': 0.7003543742015101, 'f1': [0.7956388374535504, 0.8677921508441132, 0.7891835710619003, 0.7526570048309179, 0.7147264846694119], 'avgF1': 0.7839996097719787, 'precision': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgPrecision': 0.7003543742015101, 'recall': [0.7668474051123161, 0.7664601084430674, 0.7900852052672347, 0.6034082106893881, 0.5749709414955444], 'avgRecall': 0.7003543742015101, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgAccuracy': 0.8171731034542782, 'f1': [0.8763107903750196, 0.959290608625554, 0.8648554744990689, 0.8387677085675735, 0.8124433204575152], 'avgF1': 0.8703335805049462, 'precision': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgPrecision': 0.8171731034542782, 'recall': [0.8702556158017041, 0.9217660728117738, 0.8667699457784663, 0.7223082881487219, 0.7047655947307245], 'avgRecall': 0.8171731034542782, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'adaptive', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 9000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion, Submucosal granulomas', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgAccuracy': 0.8528078183207981, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8900492682245151, 0.8737186477644493, 0.8422848050693988], 'avgF1': 0.8961204878211272, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgPrecision': 0.8528078183207981, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8919442292796282, 0.7757552285050349, 0.7489345215032933], 'avgRecall': 0.8528078183207981, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'log2', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 700, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.852808 0.896120 0.852808 0.852808
1 0.844132 0.890772 0.844132 0.844132
2 0.704227 0.787366 0.704227 0.704227
3 0.562354 0.556080 0.562354 0.562354
4 0.753577 0.824284 0.753577 0.753577
5 0.851181 0.894787 0.851181 0.851181
6 0.700354 0.784000 0.700354 0.700354
7 0.817173 0.870334 0.817173 0.817173
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'brute', 'leaf_size': 30, 'metri...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
Processing Model: RandomForestClassifier
*****************************************************
* RandomForestClassifier
* Best Params Result:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgAccuracy': 0.8528852476432826, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8908068506388271, 0.8737186477644493, 0.8420297532151674], 'avgF1': 0.8962209939331433, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgPrecision': 0.8528852476432826, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgRecall': 0.8528852476432826, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: KNeighborsClassifier
*****************************************************
* KNeighborsClassifier
* Best Params Result:
* {'classifier': 'KNeighborsClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgAccuracy': 0.8194148624083941, 'f1': [0.9172195641892283, 0.9955261622252479, 0.8653575275121729, 0.7976717112922003, 0.7702454308694038], 'avgF1': 0.8692040792176506, 'precision': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgPrecision': 0.8194148624083941, 'recall': [0.9252517428350117, 0.9910921766072812, 0.87141750580945, 0.663439194422928, 0.6458736923672995], 'avgRecall': 0.8194148624083941, 'params': [{'algorithm': 'auto', 'leaf_size': 30, 'metric': 'minkowski', 'metric_params': None, 'n_jobs': -1, 'n_neighbors': 12, 'p': 2, 'weights': 'distance'}]}
*****************************************************
Processing Model: LogisticRegression
*****************************************************
* LogisticRegression
* Best Params Result:
* {'classifier': 'LogisticRegression', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgAccuracy': 0.7043049502846728, 'f1': [0.8006471460744299, 0.8751905902853409, 0.7984777645297028, 0.7453838678328474, 0.7167332306608132], 'avgF1': 0.7872865198766268, 'precision': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgPrecision': 0.7043049502846728, 'recall': [0.7730441518202944, 0.7780790085205267, 0.7993803253292022, 0.5941130906274206, 0.5769081751259202], 'avgRecall': 0.7043049502846728, 'params': [{'C': 1, 'class_weight': None, 'dual': False, 'fit_intercept': True, 'intercept_scaling': 1, 'l1_ratio': None, 'max_iter': 100, 'multi_class': 'ovr', 'n_jobs': -1, 'penalty': 'l2', 'random_state': None, 'solver': 'newton-cg', 'tol': 0.0001, 'verbose': 0, 'warm_start': False}]}
*****************************************************
Processing Model: GaussianNB
*****************************************************
* GaussianNB
* Best Params Result:
* {'classifier': 'GaussianNB', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgAccuracy': 0.720112626651713, 'f1': [0.7820267569039114, 0.8602957404546456, 0.7642360198261849, 0.8093151948351396, 0.7764561954959115], 'avgF1': 0.7984659815031586, 'precision': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgPrecision': 0.720112626651713, 'recall': [0.7478698683191325, 0.7548412083656081, 0.7641363284275755, 0.679705654531371, 0.654010073614878], 'avgRecall': 0.720112626651713, 'params': [{'priors': None, 'var_smoothing': 1e-09}]}
*****************************************************
Processing Model: AdaBoostClassifier
*****************************************************
* AdaBoostClassifier
* Best Params Result:
* {'classifier': 'AdaBoostClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgAccuracy': 0.7531899230238491, 'f1': [0.8198695777300405, 0.8761697497279651, 0.803125804689984, 0.8247610377787892, 0.7965198184597836], 'avgF1': 0.8240891976773125, 'precision': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgPrecision': 0.7531899230238491, 'recall': [0.7989930286599535, 0.7796281951975214, 0.8036405886909372, 0.7017815646785438, 0.6819062378922898], 'avgRecall': 0.7531899230238491, 'params': [{'algorithm': 'SAMME.R', 'base_estimator': None, 'learning_rate': 1, 'n_estimators': 300, 'random_state': None}]}
*****************************************************
Processing Model: DecisionTreeClassifier
*****************************************************
* DecisionTreeClassifier
* Best Params Result:
* {'classifier': 'DecisionTreeClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgAccuracy': 0.8510259835399666, 'f1': [0.8998928645511427, 0.971109782825264, 0.8896705786217454, 0.8732271437922758, 0.8399854284829621], 'avgF1': 0.894777159654678, 'precision': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgPrecision': 0.8510259835399666, 'recall': [0.8993028659953525, 0.9438419829589465, 0.8915569326103796, 0.7749806351665376, 0.7454475009686168], 'avgRecall': 0.8510259835399666, 'params': [{'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'entropy', 'max_depth': None, 'max_features': 'auto', 'max_leaf_nodes': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'random_state': None, 'splitter': 'best'}]}
*****************************************************
Processing Model: SVC
*****************************************************
* SVC
* Best Params Result:
* {'classifier': 'SVC', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgAccuracy': 0.7216604628172689, 'f1': [0.7956388374535504, 0.8680403331871986, 0.7870196635072528, 0.7880779159821638, 0.7633072687128298], 'avgF1': 0.8004168037685991, 'precision': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgPrecision': 0.7216604628172689, 'recall': [0.7668474051123161, 0.7668474051123161, 0.7877614252517429, 0.6502711076684741, 0.6365749709414955], 'avgRecall': 0.7216604628172689, 'params': [{'C': 1.0, 'break_ties': False, 'cache_size': 4000, 'class_weight': None, 'coef0': 0.0, 'decision_function_shape': 'ovr', 'degree': 3, 'gamma': 'scale', 'kernel': 'linear', 'max_iter': -1, 'probability': False, 'random_state': None, 'shrinking': True, 'tol': 0.001, 'verbose': False}]}
*****************************************************
Processing Model: MLPClassifier
*****************************************************
* MLPClassifier
* Best Params Result:
* {'classifier': 'MLPClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgAccuracy': 0.8168642564939342, 'f1': [0.882789074745606, 0.9459073280261276, 0.8677169818543689, 0.8377222597344136, 0.8211514397895884], 'avgF1': 0.8710574168300209, 'precision': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgPrecision': 0.8168642564939342, 'recall': [0.8783888458559257, 0.8973663826491092, 0.8702556158017041, 0.7207591014717274, 0.717551336691205], 'avgRecall': 0.8168642564939342, 'params': [{'activation': 'logistic', 'alpha': 0.0001, 'batch_size': 'auto', 'beta_1': 0.9, 'beta_2': 0.999, 'early_stopping': False, 'epsilon': 1e-08, 'hidden_layer_sizes': (100,), 'learning_rate': 'constant', 'learning_rate_init': 0.001, 'max_fun': 15000, 'max_iter': 5000, 'momentum': 0.9, 'n_iter_no_change': 10, 'nesterovs_momentum': True, 'power_t': 0.5, 'random_state': None, 'shuffle': True, 'solver': 'adam', 'tol': 0.0001, 'validation_fraction': 0.1, 'verbose': False, 'warm_start': False}]}
*****************************************************
*****************************************************
* Best Performing Model and Params is:
* {'classifier': 'RandomForestClassifier', 'features': 'Marked & transmucosal increase in lamina propria cellularity, Crypt architecture, Epithelial changes, Mucosal surface, Lamina propria granulomas, Patchy lamina propria cellularity?, Mucin depletion', 'accuracy': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgAccuracy': 0.8528852476432826, 'f1': [0.9022114095895609, 0.9723383084577115, 0.8908068506388271, 0.8737186477644493, 0.8420297532151674], 'avgF1': 0.8962209939331433, 'precision': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgPrecision': 0.8528852476432826, 'recall': [0.9012393493415957, 0.9461657629744384, 0.8927188226181255, 0.7757552285050349, 0.7485470747772182], 'avgRecall': 0.8528852476432826, 'params': [{'bootstrap': True, 'ccp_alpha': 0.0, 'class_weight': None, 'criterion': 'gini', 'max_depth': None, 'max_features': 'sqrt', 'max_leaf_nodes': None, 'max_samples': None, 'min_impurity_decrease': 0.0, 'min_impurity_split': None, 'min_samples_leaf': 1, 'min_samples_split': 2, 'min_weight_fraction_leaf': 0.0, 'n_estimators': 200, 'n_jobs': -1, 'oob_score': True, 'random_state': None, 'verbose': 0, 'warm_start': False}]}
*****************************************************
model features \
0 RandomForestClassifier Marked & transmucosal increase in lamina propr...
1 KNeighborsClassifier Marked & transmucosal increase in lamina propr...
2 LogisticRegression Marked & transmucosal increase in lamina propr...
3 GaussianNB Marked & transmucosal increase in lamina propr...
4 AdaBoostClassifier Marked & transmucosal increase in lamina propr...
5 DecisionTreeClassifier Marked & transmucosal increase in lamina propr...
6 SVC Marked & transmucosal increase in lamina propr...
7 MLPClassifier Marked & transmucosal increase in lamina propr...
accuracy f1 precision recall \
0 0.852885 0.896221 0.852885 0.852885
1 0.819415 0.869204 0.819415 0.819415
2 0.704305 0.787287 0.704305 0.704305
3 0.720113 0.798466 0.720113 0.720113
4 0.753190 0.824089 0.753190 0.753190
5 0.851026 0.894777 0.851026 0.851026
6 0.721660 0.800417 0.721660 0.721660
7 0.816864 0.871057 0.816864 0.816864
params
0 {'bootstrap': True, 'ccp_alpha': 0.0, 'class_w...
1 {'algorithm': 'auto', 'leaf_size': 30, 'metric...
2 {'C': 1, 'class_weight': None, 'dual': False, ...
3 {'priors': None, 'var_smoothing': 1e-09}
4 {'algorithm': 'SAMME.R', 'base_estimator': Non...
5 {'ccp_alpha': 0.0, 'class_weight': None, 'crit...
6 {'C': 1.0, 'break_ties': False, 'cache_size': ...
7 {'activation': 'logistic', 'alpha': 0.0001, 'b...
now = datetime.datetime.now()
print ("Current date and time : ")
print (now.strftime("%Y-%m-%d %H:%M:%S"))
Current date and time : 2021-06-06 04:16:12
smotePrintoutBytes = open('smotePrintout_onlyibd.txt','r')
smotePrintout = smotePrintoutBytes.read()
smotePrintout[:100]
'********************************************\nStarting SMOTE data set....\n***************************'
originalPrintoutBytes = open('originalDatasetPrintout_onlyibd.txt','r')
originalPrintout = originalPrintoutBytes.read()
originalPrintout[:100]
'********************************************\nStarting Original data set....\n************************'
msmotePrintoutBytes = open('msmotePrintout_onlyibd.txt','r')
msmotePrintout = msmotePrintoutBytes.read()
msmotePrintout[:100]
'********************************************\nStarting MSMOTE data set....\n**************************'
'''
Using the printout from the SMOTE and original runs,
grab the dictionaries that match this format
{'classifier':'RandomForestClassifier','features':'Feature1, Feature2'}
'''
smoteModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',smotePrintout)
originalModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',originalPrintout)
msmoteModelDictionaries = re.findall('Best Params Result: \n\* \{([^}]+)\}',msmotePrintout)
'''
each dictionary is in format of 'key':'value' or 'key':[values] or 'key': 0.0002 or 'key': None
get the classifier: (text is here) ..... avgRecall : (text is here) .... avgF1 : (text is here)
'''
def getMetricsForAllModels(modelDictionaries, smote='smote'):
listOfDicts = []
for dictionary in modelDictionaries:
keys = ['classifier','avgAccuracy','avgF1','avgPrecision','avgRecall']
values = re.findall("'classifier': '([^']+)'.+'avgAccuracy': ([.\d]+).+'avgF1': ([.\d]+).+'avgPrecision': ([.\d]+).+'avgRecall': ([.\d]+)",dictionary)[0]
dictionary = dict(zip(keys,values))
dictionary['smote'] = smote
listOfDicts.append(dictionary)
return listOfDicts
smoteDictList = getMetricsForAllModels(smoteModelDictionaries,'smote')
originalDictList = getMetricsForAllModels(originalModelDictionaries,'no smote')
msmoteDictList = getMetricsForAllModels(msmoteModelDictionaries,'msmote')
def createModelCompareDf(dictList):
modelCompare = pd.DataFrame(columns = ['classifier','avgAccuracy','avgF1','avgPrecision','avgRecall'])
for dictionary in dictList:
modelCompare = modelCompare.append(dictionary, ignore_index=True)
return modelCompare
smoteCompareDf = createModelCompareDf(smoteDictList)
originalCompareDf = createModelCompareDf(originalDictList)
msmoteCompareDf = createModelCompareDf(msmoteDictList)
modelCompare = pd.concat([smoteCompareDf, originalCompareDf,msmoteCompareDf], ignore_index=True)
modelCompare.head()
| classifier | avgAccuracy | avgF1 | avgPrecision | avgRecall | smote | |
|---|---|---|---|---|---|---|
| 0 | RandomForestClassifier | 0.778552920071756 | 0.7952724325649522 | 0.778552920071756 | 0.778552920071756 | smote |
| 1 | KNeighborsClassifier | 0.7462959271809182 | 0.77386163218242 | 0.7462959271809182 | 0.7462959271809182 | smote |
| 2 | LogisticRegression | 0.648169556840077 | 0.692048322178302 | 0.648169556840077 | 0.648169556840077 | smote |
| 3 | GaussianNB | 0.5866985582353332 | 0.5370210108736294 | 0.5866985582353332 | 0.5866985582353332 | smote |
| 4 | AdaBoostClassifier | 0.7207893163244967 | 0.7549521900542933 | 0.7207893163244967 | 0.7207893163244967 | smote |
| ... | ... | ... | ... | ... | ... | ... |
| 403 | GaussianNB | 0.720112626651713 | 0.7984659815031586 | 0.720112626651713 | 0.720112626651713 | msmote |
| 404 | AdaBoostClassifier | 0.7531899230238491 | 0.8240891976773125 | 0.7531899230238491 | 0.7531899230238491 | msmote |
| 405 | DecisionTreeClassifier | 0.8510259835399666 | 0.894777159654678 | 0.8510259835399666 | 0.8510259835399666 | msmote |
| 406 | SVC | 0.7216604628172689 | 0.8004168037685991 | 0.7216604628172689 | 0.7216604628172689 | msmote |
| 407 | MLPClassifier | 0.8168642564939342 | 0.8710574168300209 | 0.8168642564939342 | 0.8168642564939342 | msmote |
408 rows × 6 columns
modelCompare[['avgAccuracy','avgF1','avgPrecision','avgRecall']] = modelCompare[['avgAccuracy','avgF1','avgPrecision','avgRecall']].astype(float)
bestModels = pd.merge(modelCompare[modelCompare['smote']=='smote'], modelCompare[modelCompare['smote']=='smote'].groupby('classifier')['avgAccuracy'].max().reset_index(), on=['classifier','avgAccuracy'])
bestModelsNo = pd.merge(modelCompare[modelCompare['smote']=='no smote'], modelCompare[modelCompare['smote']=='no smote'].groupby('classifier')['avgAccuracy'].max().reset_index(), on=['classifier','avgAccuracy'])
bestModelsM = pd.merge(modelCompare[modelCompare['smote']=='msmote'], modelCompare[modelCompare['smote']=='msmote'].groupby('classifier')['avgAccuracy','avgF1'].max().reset_index(), on=['classifier','avgAccuracy','avgF1'])
<ipython-input-277-a0afa624f181>:3: FutureWarning: Indexing with multiple keys (implicitly converted to a tuple of keys) will be deprecated, use a list instead.
rotation = 90
fig,ax=plt.subplots(nrows=2,ncols=2,figsize=(20,15))
plt.subplots_adjust(hspace=0.5)
ax[0][0].scatter(bestModels['classifier'].unique(),bestModels['avgAccuracy'].unique(),label='smote')
ax[0][0].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgAccuracy'].unique(),label='no smote')
ax[0][0].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgAccuracy'].unique(),label='msmote')
ax[0][0].tick_params(rotation=rotation)
ax[0][0].set(title='Best Accuracy for each Model')
ax[0][1].scatter(bestModels['classifier'].unique(),bestModels['avgRecall'].unique(),label='smote')
ax[0][1].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgRecall'].unique(),label='no smote')
ax[0][1].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgRecall'].unique(),label='msmote')
ax[0][1].tick_params(rotation=rotation)
ax[0][1].set(title='Recall(Sensitivity) for Models with best Accuracy')
ax[0][1].legend()
ax[1][0].scatter(bestModels['classifier'].unique(),bestModels['avgF1'].unique(),
label='smote')
ax[1][0].scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgF1'].unique(),label='no smote')
ax[1][0].scatter(bestModelsM['classifier'].unique(),bestModelsM['avgF1'].unique(),label='msmote')
ax[1][0].tick_params(rotation=rotation)
ax[1][0].set(title='F1 for Models with best Accuracy')
ax[1][0].legend()
for classifier in modelCompare['classifier'].unique():
subdf = modelCompare[modelCompare['classifier']==classifier]
ax[1][1].scatter(subdf['avgF1'],subdf['avgAccuracy'],label=classifier)
ax[1][1].set(xlabel='F1',ylabel='avgAccuracy',title='Each point is the Average of 5 fold Runs for each algorithm at a specific feature set/parameter set')
ax[1][1].legend(bbox_to_anchor=(1.4,0.5))
<matplotlib.legend.Legend at 0x22b3ff5e910>
fig,ax=plt.subplots()
ax.scatter(bestModels['classifier'].unique(),bestModels['avgRecall'].unique(),label='smote')
ax.scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgRecall'].unique(),label='no smote')
ax.scatter(bestModelsM['classifier'].unique(),bestModelsM['avgRecall'].unique(),label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Precision/Recall for Models with best Accuracy')
ax.legend()
<matplotlib.legend.Legend at 0x22b40793e20>
fig,ax=plt.subplots()
ax.scatter(bestModels['classifier'].unique(),bestModels['avgF1'].unique(),label='smote')
ax.scatter(bestModelsNo['classifier'].unique(),bestModelsNo['avgF1'].unique(),label='no smote')
ax.scatter(bestModelsM['classifier'].unique(),bestModelsM['avgF1'].unique(),label='msmote')
ax.tick_params(rotation=90)
ax.set(title='F1 for Models with best Accuracy')
ax.legend()
<matplotlib.legend.Legend at 0x22b4071c2e0>
fig,ax=plt.subplots()
for classifier in modelCompare['classifier'].unique():
subdf = modelCompare[modelCompare['classifier']==classifier]
ax.scatter(subdf['avgAccuracy'],subdf['avgF1'],label=classifier)
ax.set(xlabel='Accuracy',ylabel='F1',title='Each point is the Average of 5 fold Runs for each algorithm at a specific feature set/parameter set')
ax.legend(bbox_to_anchor=(1.4,0.5))
<matplotlib.legend.Legend at 0x22b408d8eb0>
classifiers = list(bestModels['classifier'].unique())
f1s = list(bestModels['avgPrecision'].astype(float).unique())
classifiers2 = list(bestModelsNo['classifier'].unique())
f1s2 = list(bestModelsNo['avgPrecision'].astype(float).unique())
classifiers3 = list(bestModelsM['classifier'].unique())
f1s3 = list(bestModelsM['avgPrecision'].astype(float).unique())
fig,ax=plt.subplots()
ax.scatter(classifiers,f1s,label='smote')
ax.scatter(classifiers2,f1s2,label='no smote')
ax.scatter(classifiers3,f1s3,label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Precision for Models with best Accuracy')
ax.legend()
<matplotlib.legend.Legend at 0x22b41fe1850>
classifiers = list(bestModels['classifier'].unique())
f1s = list(bestModels['avgAccuracy'].astype(float).unique())
classifiers2 = list(bestModelsNo['classifier'].unique())
f1s2 = list(bestModelsNo['avgAccuracy'].astype(float).unique())
classifiers3 = list(bestModelsM['classifier'].unique())
f1s3 = list(bestModelsM['avgAccuracy'].astype(float).unique())
fig,ax=plt.subplots()
ax.scatter(classifiers,f1s,label='smote')
ax.scatter(classifiers2,f1s2,label='no smote')
ax.scatter(classifiers3,f1s3,label='msmote')
ax.tick_params(rotation=90)
ax.set(title='Best Accuracy for each Model')
ax.legend(bbox_to_anchor=(1.4,0.5))
<matplotlib.legend.Legend at 0x22b4203c9a0>
bestRf = pd.merge( modelCompare,
modelCompare[modelCompare['classifier']=='RandomForestClassifier'].groupby(['smote','classifier'])['avgAccuracy'].max().reset_index(),
on = ['classifier','avgAccuracy'])
fig,ax= plt.subplots()
ax.scatter(bestRf['smote_x'],bestRf['avgF1'],label='f1')
ax.scatter(bestRf['smote_x'],bestRf['avgRecall']+0.001,label='recall')
ax.scatter(bestRf['smote_x'],bestRf['avgPrecision'],label='precision')
ax.scatter(bestRf['smote_x'],bestRf['avgAccuracy'],label='accuracy')
ax.set(ylabel='metric value')
ax.legend(bbox_to_anchor=(1.4,0.5))
ax.set(ylim=[0.5,1])
ax.set(title='Best SMOTE vs Best No Smote Models for Random Forest (the best out of all models)')
[Text(0.5, 1.0, 'Best SMOTE vs Best No Smote Models for Random Forest (the best out of all models)')]
bestRf
| classifier | avgAccuracy | avgF1 | avgPrecision | avgRecall | smote_x | smote_y | |
|---|---|---|---|---|---|---|---|
| 0 | RandomForestClassifier | 0.781981 | 0.797991 | 0.781981 | 0.781981 | smote | smote |
| 1 | RandomForestClassifier | 0.757655 | 0.738540 | 0.757655 | 0.757655 | no smote | no smote |
| 2 | RandomForestClassifier | 0.988380 | 0.989054 | 0.988380 | 0.988380 | msmote | msmote |
| 3 | RandomForestClassifier | 0.988380 | 0.989047 | 0.988380 | 0.988380 | msmote | msmote |
'''
acc
recall
f1
precision
'''
'\n\nacc \nrecall\nf1\nprecision\n\n'
fig,ax=plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
[0.781981, 0.797991, 0.781981, 0.781981], label='smote')
ax.set(xlim=[0.7,0.9])
[(0.7, 0.9)]
fig,ax= plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
[0.757655, 0.738540, 0.757655, 0.757655], label='no smote')
ax.set(xlim=[0.7, 0.9])
[(0.7, 0.9)]
fig,ax= plt.subplots()
ax.barh(['accuracy','f1','recall','precision'],
[0.988380, 0.989054, 0.988380, 0.988380], label='msmote')
ax.set(xlim=[0.7, 0.9])
[(0.7, 0.9)]